sherpa-onnx/sherpa_onnx_with_models_from_wenet.ipynb

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      "provenance": [],
      "toc_visible": true,
      "authorship_tag": "ABX9TyN+IhuE4Nkfqgv7C+cDUmKn",
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      "name": "python3",
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
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      "source": [
        "<a href=\"https://colab.research.google.com/github/k2-fsa/colab/blob/master/sherpa-onnx/sherpa_onnx_with_models_from_wenet.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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    {
      "cell_type": "markdown",
      "source": [
        "# Introduction\n",
        "\n",
        "This colab notebooks shows how to use [sherpa-onnx](https://github.com/k2-fsa/sherpa-onnx) with models with\n",
        "[WeNet](https://github.com/wenet-e2e/wenet)."
      ],
      "metadata": {
        "id": "6oZpJxRWIMnw"
      }
    },
    {
      "cell_type": "markdown",
      "source": [
        "Please see\n",
        "\n",
        "https://k2-fsa.github.io/sherpa/onnx/pretrained_models/wenet/index.html\n",
        "\n",
        "for details"
      ],
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        "id": "Q6UhkFk_OaQk"
      }
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            "[ 14%] \u001b[32mBuilding C object _deps/portaudio-build/CMakeFiles/portaudio_static.dir/src/common/pa_front.c.o\u001b[0m\n",
            "[ 14%] \u001b[32mBuilding C object _deps/portaudio-build/CMakeFiles/portaudio_static.dir/src/common/pa_process.c.o\u001b[0m\n",
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            "[ 16%] \u001b[32mBuilding C object _deps/portaudio-build/CMakeFiles/portaudio_static.dir/src/os/unix/pa_unix_hostapis.c.o\u001b[0m\n",
            "[ 18%] \u001b[32mBuilding C object _deps/portaudio-build/CMakeFiles/portaudio_static.dir/src/os/unix/pa_unix_util.c.o\u001b[0m\n",
            "[ 18%] \u001b[32mBuilding C object _deps/portaudio-build/CMakeFiles/portaudio_static.dir/src/hostapi/jack/pa_jack.c.o\u001b[0m\n",
            "[ 18%] \u001b[32mBuilding C object _deps/portaudio-build/CMakeFiles/portaudio_static.dir/src/hostapi/alsa/pa_linux_alsa.c.o\u001b[0m\n",
            "[ 18%] \u001b[32m\u001b[1mLinking C static library ../../lib/libcargs.a\u001b[0m\n",
            "[ 18%] Built target cargs\n",
            "\u001b[01m\u001b[K/content/sherpa-onnx/build/_deps/portaudio-src/src/hostapi/alsa/pa_linux_alsa.c:\u001b[m\u001b[K In function ‘\u001b[01m\u001b[KBuildDeviceList.constprop\u001b[m\u001b[K’:\n",
            "\u001b[01m\u001b[K/content/sherpa-onnx/build/_deps/portaudio-src/src/hostapi/alsa/pa_linux_alsa.c:1304:45:\u001b[m\u001b[K \u001b[01;35m\u001b[Kwarning: \u001b[m\u001b[K‘\u001b[01m\u001b[K%s\u001b[m\u001b[K’ directive output may be truncated writing up to 49 bytes into a region of size between 46 and 50 [\u001b[01;35m\u001b[K\u001b]8;;https://gcc.gnu.org/onlinedocs/gcc/Warning-Options.html#index-Wformat-truncation=\u0007-Wformat-truncation=\u001b]8;;\u0007\u001b[m\u001b[K]\n",
            " 1304 |             snprintf( buf, sizeof (buf), \"%s\u001b[01;35m\u001b[K%s\u001b[m\u001b[K,%d\", hwPrefix, \u001b[32m\u001b[KalsaCardName\u001b[m\u001b[K, devIdx );\n",
            "      |                                             \u001b[01;35m\u001b[K^~\u001b[m\u001b[K                \u001b[32m\u001b[K~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "\u001b[01m\u001b[K/content/sherpa-onnx/build/_deps/portaudio-src/src/hostapi/alsa/pa_linux_alsa.c:1304:42:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[Kdirective argument in the range [0, 2147483647]\n",
            " 1304 |             snprintf( buf, sizeof (buf), \u001b[01;36m\u001b[K\"%s%s,%d\"\u001b[m\u001b[K, hwPrefix, alsaCardName, devIdx );\n",
            "      |                                          \u001b[01;36m\u001b[K^~~~~~~~~\u001b[m\u001b[K\n",
            "In file included from \u001b[01m\u001b[K/usr/include/stdio.h:894\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/usr/include/alsa/asoundlib.h:32\u001b[m\u001b[K,\n",
            "                 from \u001b[01m\u001b[K/content/sherpa-onnx/build/_deps/portaudio-src/src/hostapi/alsa/pa_linux_alsa.c:52\u001b[m\u001b[K:\n",
            "\u001b[01m\u001b[K/usr/include/x86_64-linux-gnu/bits/stdio2.h:71:10:\u001b[m\u001b[K \u001b[01;36m\u001b[Knote: \u001b[m\u001b[K‘\u001b[01m\u001b[K__builtin___snprintf_chk\u001b[m\u001b[K’ output between 3 and 65 bytes into a destination of size 50\n",
            "   71 |   return \u001b[01;36m\u001b[K__builtin___snprintf_chk (__s, __n, __USE_FORTIFY_LEVEL - 1,\u001b[m\u001b[K\n",
            "      |          \u001b[01;36m\u001b[K^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~\u001b[m\u001b[K\n",
            "   72 | \u001b[01;36m\u001b[K                                   __glibc_objsize (__s), __fmt,\u001b[m\u001b[K\n",
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            "   73 | \u001b[01;36m\u001b[K                                   __va_arg_pack ())\u001b[m\u001b[K;\n",
            "      |                                    \u001b[01;36m\u001b[K~~~~~~~~~~~~~~~~~\u001b[m\u001b[K\n",
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            "[ 79%] Built target sherpa-onnx-core\n",
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            "[ 91%] \u001b[32mBuilding CXX object sherpa-onnx/csrc/CMakeFiles/sherpa-onnx-online-websocket-client.dir/online-websocket-client.cc.o\u001b[0m\n",
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            "[ 93%] \u001b[32mBuilding CXX object sherpa-onnx/c-api/CMakeFiles/sherpa-onnx-c-api.dir/c-api.cc.o\u001b[0m\n",
            "[ 93%] \u001b[32m\u001b[1mLinking CXX executable ../../bin/sherpa-onnx-offline-tts\u001b[0m\n",
            "[ 93%] \u001b[32m\u001b[1mLinking CXX executable ../../bin/sherpa-onnx-vad-microphone\u001b[0m\n",
            "[ 93%] \u001b[32m\u001b[1mLinking CXX executable ../../bin/sherpa-onnx-offline\u001b[0m\n",
            "[ 93%] \u001b[32m\u001b[1mLinking CXX executable ../../bin/sherpa-onnx-vad-microphone-offline-asr\u001b[0m\n",
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            "[ 95%] \u001b[32m\u001b[1mLinking CXX executable ../../bin/sherpa-onnx-microphone\u001b[0m\n",
            "[ 95%] \u001b[32m\u001b[1mLinking CXX executable ../../bin/sherpa-onnx-alsa\u001b[0m\n",
            "[ 95%] \u001b[32m\u001b[1mLinking CXX executable ../../bin/sherpa-onnx\u001b[0m\n",
            "[ 97%] \u001b[32m\u001b[1mLinking CXX executable ../../bin/sherpa-onnx-offline-parallel\u001b[0m\n",
            "[ 97%] \u001b[32m\u001b[1mLinking CXX static library ../../lib/libsherpa-onnx-c-api.a\u001b[0m\n",
            "[ 97%] Built target sherpa-onnx-c-api\n",
            "[ 97%] \u001b[32mBuilding C object c-api-examples/CMakeFiles/decode-file-c-api.dir/decode-file-c-api.c.o\u001b[0m\n",
            "[ 97%] \u001b[32mBuilding C object c-api-examples/CMakeFiles/offline-tts-c-api.dir/offline-tts-c-api.c.o\u001b[0m\n",
            "[ 97%] \u001b[32m\u001b[1mLinking CXX executable ../bin/offline-tts-c-api\u001b[0m\n",
            "[100%] \u001b[32m\u001b[1mLinking CXX executable ../bin/decode-file-c-api\u001b[0m\n",
            "[100%] Built target sherpa-onnx-vad-microphone\n",
            "[100%] Built target sherpa-onnx-offline-tts\n",
            "[100%] Built target sherpa-onnx-offline\n",
            "[100%] Built target sherpa-onnx-vad-microphone-offline-asr\n",
            "[100%] Built target sherpa-onnx-microphone-offline\n",
            "[100%] Built target sherpa-onnx-microphone\n",
            "[100%] Built target sherpa-onnx-alsa\n",
            "[100%] Built target sherpa-onnx\n",
            "[100%] Built target sherpa-onnx-offline-parallel\n",
            "[100%] Built target decode-file-c-api\n",
            "[100%] Built target offline-tts-c-api\n",
            "[100%] \u001b[32m\u001b[1mLinking CXX executable ../../bin/sherpa-onnx-offline-websocket-server\u001b[0m\n",
            "[100%] \u001b[32m\u001b[1mLinking CXX executable ../../bin/sherpa-onnx-online-websocket-server\u001b[0m\n",
            "[100%] \u001b[32m\u001b[1mLinking CXX executable ../../bin/sherpa-onnx-online-websocket-client\u001b[0m\n",
            "[100%] Built target sherpa-onnx-online-websocket-client\n",
            "[100%] Built target sherpa-onnx-offline-websocket-server\n",
            "[100%] Built target sherpa-onnx-online-websocket-server\n",
            "total 317M\n",
            "-rwxr-xr-x 1 root root  26M Nov 16 03:49 decode-file-c-api\n",
            "-rwxr-xr-x 1 root root  26M Nov 16 03:49 offline-tts-c-api\n",
            "-rwxr-xr-x 1 root root  23M Nov 16 03:49 sherpa-onnx\n",
            "-rwxr-xr-x 1 root root  23M Nov 16 03:49 sherpa-onnx-alsa\n",
            "-rwxr-xr-x 1 root root  24M Nov 16 03:49 sherpa-onnx-microphone\n",
            "-rwxr-xr-x 1 root root  25M Nov 16 03:49 sherpa-onnx-microphone-offline\n",
            "-rwxr-xr-x 1 root root  25M Nov 16 03:49 sherpa-onnx-offline\n",
            "-rwxr-xr-x 1 root root  25M Nov 16 03:49 sherpa-onnx-offline-parallel\n",
            "-rwxr-xr-x 1 root root  25M Nov 16 03:49 sherpa-onnx-offline-tts\n",
            "-rwxr-xr-x 1 root root  25M Nov 16 03:50 sherpa-onnx-offline-websocket-server\n",
            "-rwxr-xr-x 1 root root 3.5M Nov 16 03:50 sherpa-onnx-online-websocket-client\n",
            "-rwxr-xr-x 1 root root  24M Nov 16 03:50 sherpa-onnx-online-websocket-server\n",
            "-rwxr-xr-x 1 root root  23M Nov 16 03:49 sherpa-onnx-vad-microphone\n",
            "-rwxr-xr-x 1 root root  25M Nov 16 03:49 sherpa-onnx-vad-microphone-offline-asr\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 1
        }
      ],
      "source": [
        "%%shell\n",
        "\n",
        "# Install sherpa-onnx\n",
        "git clone https://github.com/k2-fsa/sherpa-onnx\n",
        "cd sherpa-onnx\n",
        "mkdir build\n",
        "cd build\n",
        "cmake ..\n",
        "make -j\n",
        "ls -lh bin"
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# sherpa-onnx-zh-wenet-aishell"
      ],
      "metadata": {
        "id": "eH5Tv8tqKQIP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "git lfs install\n",
        "git clone https://huggingface.co/csukuangfj/sherpa-onnx-zh-wenet-aishell\n",
        "ls -lh sherpa-onnx-zh-wenet-aishell"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "M549GQnTInNp",
        "outputId": "68152b57-1cc6-441d-a563-dd930c0d52af"
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Git LFS initialized.\n",
            "Cloning into 'sherpa-onnx-zh-wenet-aishell'...\n",
            "remote: Enumerating objects: 24, done.\u001b[K\n",
            "remote: Counting objects:   4% (1/21)\u001b[K\rremote: Counting objects:   9% (2/21)\u001b[K\rremote: Counting objects:  14% (3/21)\u001b[K\rremote: Counting objects:  19% (4/21)\u001b[K\rremote: Counting objects:  23% (5/21)\u001b[K\rremote: Counting objects:  28% (6/21)\u001b[K\rremote: Counting objects:  33% (7/21)\u001b[K\rremote: Counting objects:  38% (8/21)\u001b[K\rremote: Counting objects:  42% (9/21)\u001b[K\rremote: Counting objects:  47% (10/21)\u001b[K\rremote: Counting objects:  52% (11/21)\u001b[K\rremote: Counting objects:  57% (12/21)\u001b[K\rremote: Counting objects:  61% (13/21)\u001b[K\rremote: Counting objects:  66% (14/21)\u001b[K\rremote: Counting objects:  71% (15/21)\u001b[K\rremote: Counting objects:  76% (16/21)\u001b[K\rremote: Counting objects:  80% (17/21)\u001b[K\rremote: Counting objects:  85% (18/21)\u001b[K\rremote: Counting objects:  90% (19/21)\u001b[K\rremote: Counting objects:  95% (20/21)\u001b[K\rremote: Counting objects: 100% (21/21)\u001b[K\rremote: Counting objects: 100% (21/21), done.\u001b[K\n",
            "remote: Compressing objects: 100% (20/20), done.\u001b[K\n",
            "remote: Total 24 (delta 1), reused 0 (delta 0), pack-reused 3\u001b[K\n",
            "Unpacking objects: 100% (24/24), 362.77 KiB | 5.95 MiB/s, done.\n",
            "Filtering content: 100% (4/4), 368.82 MiB | 43.46 MiB/s, done.\n",
            "total 369M\n",
            "-rw-r--r-- 1 root root  48M Nov 16 03:50 model.int8.onnx\n",
            "-rw-r--r-- 1 root root 138M Nov 16 03:50 model.onnx\n",
            "-rw-r--r-- 1 root root  48M Nov 16 03:50 model-streaming.int8.onnx\n",
            "-rw-r--r-- 1 root root 137M Nov 16 03:50 model-streaming.onnx\n",
            "-rw-r--r-- 1 root root  130 Nov 16 03:50 README.md\n",
            "drwxr-xr-x 2 root root 4.0K Nov 16 03:50 test_wavs\n",
            "-rwxr-xr-x 1 root root  37K Nov 16 03:50 tokens.txt\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 2
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Streaming decoding"
      ],
      "metadata": {
        "id": "ms0zjhn2KgEi"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# float32 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-zh-wenet-aishell/model-streaming.onnx \\\n",
        "  --tokens=./sherpa-onnx-zh-wenet-aishell/tokens.txt \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5sCJn2iaKcx3",
        "outputId": "3697a13a-a5ed-4ebb-d444-bdd4680535e1"
      },
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx --wenet-ctc-model=./sherpa-onnx-zh-wenet-aishell/model-streaming.onnx --tokens=./sherpa-onnx-zh-wenet-aishell/tokens.txt ./sherpa-onnx-zh-wenet-aishell/test_wavs/0.wav ./sherpa-onnx-zh-wenet-aishell/test_wavs/1.wav ./sherpa-onnx-zh-wenet-aishell/test_wavs/8k.wav \n",
            "\n",
            "OnlineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OnlineModelConfig(transducer=OnlineTransducerModelConfig(encoder=\"\", decoder=\"\", joiner=\"\"), paraformer=OnlineParaformerModelConfig(encoder=\"\", decoder=\"\"), wenet_ctc=OnlineWenetCtcModelConfig(model=\"./sherpa-onnx-zh-wenet-aishell/model-streaming.onnx\", chunk_size=16, num_left_chunks=4), tokens=\"./sherpa-onnx-zh-wenet-aishell/tokens.txt\", num_threads=1, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OnlineLMConfig(model=\"\", scale=0.5), endpoint_config=EndpointConfig(rule1=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=2.4, min_utterance_length=0), rule2=EndpointRule(must_contain_nonsilence=True, min_trailing_silence=1.2, min_utterance_length=0), rule3=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=0, min_utterance_length=20)), enable_endpoint=True, max_active_paths=4, hotwords_score=1.5, hotwords_file=\"\", decoding_method=\"greedy_search\")\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/features.cc:AcceptWaveformImpl:85 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "./sherpa-onnx-zh-wenet-aishell/test_wavs/0.wav\n",
            "Elapsed seconds: 1.1, Real time factor (RTF): 0.2\n",
            "对我做了介绍马偶想说的来量如果练了研究感兴趣\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"对我做了介绍马偶想说的来量如果练了研究感兴趣\", \"timestamps\": [0.52, 0.04, 0.20, 0.32, 0.48, 0.04, 0.20, 0.40, 0.56, 0.08, 0.16, 0.28, 0.40, 0.52, 0.00, 0.12, 0.24, 0.36, 0.48, 0.00, 0.24, 0.44], \"tokens\":[\"对\", \"我\", \"做\", \"了\", \"介\", \"绍\", \"马\", \"偶\", \"想\", \"说\", \"的\", \"来\", \"量\", \"如\", \"果\", \"练\", \"了\", \"研\", \"究\", \"感\", \"兴\", \"趣\"]}\n",
            "\n",
            "./sherpa-onnx-zh-wenet-aishell/test_wavs/1.wav\n",
            "Elapsed seconds: 1.1, Real time factor (RTF): 0.22\n",
            "痛点了小看三个问题首先那就是这一轮全球电动动荡的表现\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"痛点了小看三个问题首先那就是这一轮全球电动动荡的表现\", \"timestamps\": [0.36, 0.52, 0.00, 0.20, 0.36, 0.52, 0.00, 0.16, 0.40, 0.48, 0.00, 0.12, 0.28, 0.48, 0.08, 0.16, 0.36, 0.56, 0.08, 0.20, 0.28, 0.44, 0.52, 0.04, 0.24, 0.44], \"tokens\":[\"痛\", \"点\", \"了\", \"小\", \"看\", \"三\", \"个\", \"问\", \"题\", \"首\", \"先\", \"那\", \"就\", \"是\", \"这\", \"一\", \"轮\", \"全\", \"球\", \"电\", \"动\", \"动\", \"荡\", \"的\", \"表\", \"现\"]}\n",
            "\n",
            "./sherpa-onnx-zh-wenet-aishell/test_wavs/8k.wav\n",
            "Elapsed seconds: 1.1, Real time factor (RTF): 0.23\n",
            "深穆的可须被喝全球金融动荡背后的根远\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"深穆的可须被喝全球金融动荡背后的根远\", \"timestamps\": [0.00, 0.12, 0.28, 0.44, 0.16, 0.60, 0.36, 0.24, 0.44, 0.56, 0.04, 0.20, 0.36, 0.48, 0.60, 0.08, 0.24, 0.48], \"tokens\":[\"深\", \"穆\", \"的\", \"可\", \"须\", \"被\", \"喝\", \"全\", \"球\", \"金\", \"融\", \"动\", \"荡\", \"背\", \"后\", \"的\", \"根\", \"远\"]}\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# int8 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-zh-wenet-aishell/model-streaming.int8.onnx \\\n",
        "  --tokens=./sherpa-onnx-zh-wenet-aishell/tokens.txt \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cOMfRV0PKyr_",
        "outputId": "b3ed4987-10d4-434b-9512-a0136635d077"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx --wenet-ctc-model=./sherpa-onnx-zh-wenet-aishell/model-streaming.int8.onnx --tokens=./sherpa-onnx-zh-wenet-aishell/tokens.txt ./sherpa-onnx-zh-wenet-aishell/test_wavs/0.wav ./sherpa-onnx-zh-wenet-aishell/test_wavs/1.wav ./sherpa-onnx-zh-wenet-aishell/test_wavs/8k.wav \n",
            "\n",
            "OnlineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OnlineModelConfig(transducer=OnlineTransducerModelConfig(encoder=\"\", decoder=\"\", joiner=\"\"), paraformer=OnlineParaformerModelConfig(encoder=\"\", decoder=\"\"), wenet_ctc=OnlineWenetCtcModelConfig(model=\"./sherpa-onnx-zh-wenet-aishell/model-streaming.int8.onnx\", chunk_size=16, num_left_chunks=4), tokens=\"./sherpa-onnx-zh-wenet-aishell/tokens.txt\", num_threads=1, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OnlineLMConfig(model=\"\", scale=0.5), endpoint_config=EndpointConfig(rule1=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=2.4, min_utterance_length=0), rule2=EndpointRule(must_contain_nonsilence=True, min_trailing_silence=1.2, min_utterance_length=0), rule3=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=0, min_utterance_length=20)), enable_endpoint=True, max_active_paths=4, hotwords_score=1.5, hotwords_file=\"\", decoding_method=\"greedy_search\")\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/features.cc:AcceptWaveformImpl:85 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "./sherpa-onnx-zh-wenet-aishell/test_wavs/0.wav\n",
            "Elapsed seconds: 1, Real time factor (RTF): 0.18\n",
            "对我做了介绍马偶想说的呢来量如果队了研究感兴趣\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"对我做了介绍马偶想说的呢来量如果队了研究感兴趣\", \"timestamps\": [0.52, 0.04, 0.20, 0.32, 0.48, 0.04, 0.20, 0.40, 0.56, 0.08, 0.16, 0.44, 0.28, 0.40, 0.52, 0.00, 0.12, 0.24, 0.36, 0.48, 0.00, 0.24, 0.44], \"tokens\":[\"对\", \"我\", \"做\", \"了\", \"介\", \"绍\", \"马\", \"偶\", \"想\", \"说\", \"的\", \"呢\", \"来\", \"量\", \"如\", \"果\", \"队\", \"了\", \"研\", \"究\", \"感\", \"兴\", \"趣\"]}\n",
            "\n",
            "./sherpa-onnx-zh-wenet-aishell/test_wavs/1.wav\n",
            "Elapsed seconds: 1, Real time factor (RTF): 0.19\n",
            "动点了小看三个问题首先那这是这一轮全球电动动荡的表现\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"动点了小看三个问题首先那这是这一轮全球电动动荡的表现\", \"timestamps\": [0.36, 0.52, 0.00, 0.20, 0.36, 0.52, 0.00, 0.16, 0.40, 0.48, 0.00, 0.12, 0.28, 0.48, 0.08, 0.16, 0.36, 0.56, 0.08, 0.20, 0.28, 0.44, 0.52, 0.04, 0.24, 0.44], \"tokens\":[\"动\", \"点\", \"了\", \"小\", \"看\", \"三\", \"个\", \"问\", \"题\", \"首\", \"先\", \"那\", \"这\", \"是\", \"这\", \"一\", \"轮\", \"全\", \"球\", \"电\", \"动\", \"动\", \"荡\", \"的\", \"表\", \"现\"]}\n",
            "\n",
            "./sherpa-onnx-zh-wenet-aishell/test_wavs/8k.wav\n",
            "Elapsed seconds: 0.94, Real time factor (RTF): 0.21\n",
            "深穆的喷须被喝全球金融动荡背后的根远\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"深穆的喷须被喝全球金融动荡背后的根远\", \"timestamps\": [0.00, 0.12, 0.28, 0.44, 0.16, 0.60, 0.36, 0.24, 0.44, 0.56, 0.04, 0.20, 0.36, 0.48, 0.60, 0.08, 0.24, 0.48], \"tokens\":[\"深\", \"穆\", \"的\", \"喷\", \"须\", \"被\", \"喝\", \"全\", \"球\", \"金\", \"融\", \"动\", \"荡\", \"背\", \"后\", \"的\", \"根\", \"远\"]}\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Non-stremaing decoding"
      ],
      "metadata": {
        "id": "Z_l3D_-MLGCl"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# float32 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx-offline \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-zh-wenet-aishell/model.onnx \\\n",
        "  --tokens=./sherpa-onnx-zh-wenet-aishell/tokens.txt \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "HV_uS00MK-us",
        "outputId": "aef44331-dd2f-4424-9211-b69bad4d61fa"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx-offline --wenet-ctc-model=./sherpa-onnx-zh-wenet-aishell/model.onnx --tokens=./sherpa-onnx-zh-wenet-aishell/tokens.txt ./sherpa-onnx-zh-wenet-aishell/test_wavs/0.wav ./sherpa-onnx-zh-wenet-aishell/test_wavs/1.wav ./sherpa-onnx-zh-wenet-aishell/test_wavs/8k.wav \n",
            "\n",
            "OfflineRecognizerConfig(feat_config=OfflineFeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename=\"\", decoder_filename=\"\", joiner_filename=\"\"), paraformer=OfflineParaformerModelConfig(model=\"\"), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=\"\"), whisper=OfflineWhisperModelConfig(encoder=\"\", decoder=\"\", language=\"\", task=\"transcribe\"), tdnn=OfflineTdnnModelConfig(model=\"\"), zipformer_ctc=OfflineZipformerCtcModelConfig(model=\"\"), wenet_ctc=OfflineWenetCtcModelConfig(model=\"./sherpa-onnx-zh-wenet-aishell/model.onnx\"), tokens=\"./sherpa-onnx-zh-wenet-aishell/tokens.txt\", num_threads=2, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OfflineLMConfig(model=\"\", scale=0.5), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph=\"\", max_active=3000), decoding_method=\"greedy_search\", max_active_paths=4, hotwords_file=\"\", hotwords_score=1.5)\n",
            "Creating recognizer ...\n",
            "Started\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/offline-stream.cc:AcceptWaveformImpl:113 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "Done!\n",
            "\n",
            "./sherpa-onnx-zh-wenet-aishell/test_wavs/0.wav\n",
            "{\"text\": \"对我做了介绍猫偶想说的事那让如果做了研究感兴趣\", \"timestamps\": [0.52, 0.68, 0.84, 0.96, 1.12, 1.32, 2.12, 2.32, 2.48, 2.60, 2.72, 2.84, 3.44, 3.60, 3.72, 3.84, 3.96, 4.08, 4.20, 4.32, 4.48, 4.72, 4.92], \"tokens\":[\"对\", \"我\", \"做\", \"了\", \"介\", \"绍\", \"猫\", \"偶\", \"想\", \"说\", \"的\", \"事\", \"那\", \"让\", \"如\", \"果\", \"做\", \"了\", \"研\", \"究\", \"感\", \"兴\", \"趣\"]}\n",
            "----\n",
            "./sherpa-onnx-zh-wenet-aishell/test_wavs/1.wav\n",
            "{\"text\": \"动点了小看三个问题首先那就是这一轮全球金动荡的表现\", \"timestamps\": [0.36, 0.52, 0.64, 0.84, 1.00, 1.16, 1.28, 1.44, 1.64, 2.40, 2.52, 2.68, 2.84, 3.04, 3.28, 3.36, 3.52, 3.76, 3.92, 4.04, 4.12, 4.36, 4.52, 4.72, 4.88], \"tokens\":[\"动\", \"点\", \"了\", \"小\", \"看\", \"三\", \"个\", \"问\", \"题\", \"首\", \"先\", \"那\", \"就\", \"是\", \"这\", \"一\", \"轮\", \"全\", \"球\", \"金\", \"动\", \"荡\", \"的\", \"表\", \"现\"]}\n",
            "----\n",
            "./sherpa-onnx-zh-wenet-aishell/test_wavs/8k.wav\n",
            "{\"text\": \"深度的分烯对于和全球金融动荡背忘地根远\", \"timestamps\": [0.60, 0.76, 0.92, 1.08, 1.44, 1.84, 2.00, 2.28, 2.80, 3.00, 3.12, 3.24, 3.40, 3.56, 3.68, 3.80, 3.92, 4.08, 4.28], \"tokens\":[\"深\", \"度\", \"的\", \"分\", \"烯\", \"对\", \"于\", \"和\", \"全\", \"球\", \"金\", \"融\", \"动\", \"荡\", \"背\", \"忘\", \"地\", \"根\", \"远\"]}\n",
            "----\n",
            "num threads: 2\n",
            "decoding method: greedy_search\n",
            "Elapsed seconds: 0.731 s\n",
            "Real time factor (RTF): 0.731 / 15.289 = 0.048\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# int8 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx-offline \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-zh-wenet-aishell/model.int8.onnx \\\n",
        "  --tokens=./sherpa-onnx-zh-wenet-aishell/tokens.txt \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "K7LH2u33LK1_",
        "outputId": "250f9fc0-29b1-43cd-e76b-23b25c834555"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx-offline --wenet-ctc-model=./sherpa-onnx-zh-wenet-aishell/model.int8.onnx --tokens=./sherpa-onnx-zh-wenet-aishell/tokens.txt ./sherpa-onnx-zh-wenet-aishell/test_wavs/0.wav ./sherpa-onnx-zh-wenet-aishell/test_wavs/1.wav ./sherpa-onnx-zh-wenet-aishell/test_wavs/8k.wav \n",
            "\n",
            "OfflineRecognizerConfig(feat_config=OfflineFeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename=\"\", decoder_filename=\"\", joiner_filename=\"\"), paraformer=OfflineParaformerModelConfig(model=\"\"), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=\"\"), whisper=OfflineWhisperModelConfig(encoder=\"\", decoder=\"\", language=\"\", task=\"transcribe\"), tdnn=OfflineTdnnModelConfig(model=\"\"), zipformer_ctc=OfflineZipformerCtcModelConfig(model=\"\"), wenet_ctc=OfflineWenetCtcModelConfig(model=\"./sherpa-onnx-zh-wenet-aishell/model.int8.onnx\"), tokens=\"./sherpa-onnx-zh-wenet-aishell/tokens.txt\", num_threads=2, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OfflineLMConfig(model=\"\", scale=0.5), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph=\"\", max_active=3000), decoding_method=\"greedy_search\", max_active_paths=4, hotwords_file=\"\", hotwords_score=1.5)\n",
            "Creating recognizer ...\n",
            "Started\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/offline-stream.cc:AcceptWaveformImpl:113 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "Done!\n",
            "\n",
            "./sherpa-onnx-zh-wenet-aishell/test_wavs/0.wav\n",
            "{\"text\": \"对我做了介绍马偶想说的事来让如果做了研究感兴趣\", \"timestamps\": [0.52, 0.68, 0.84, 0.96, 1.12, 1.32, 2.12, 2.32, 2.48, 2.60, 2.72, 2.84, 3.44, 3.60, 3.72, 3.84, 3.96, 4.08, 4.20, 4.32, 4.48, 4.72, 4.92], \"tokens\":[\"对\", \"我\", \"做\", \"了\", \"介\", \"绍\", \"马\", \"偶\", \"想\", \"说\", \"的\", \"事\", \"来\", \"让\", \"如\", \"果\", \"做\", \"了\", \"研\", \"究\", \"感\", \"兴\", \"趣\"]}\n",
            "----\n",
            "./sherpa-onnx-zh-wenet-aishell/test_wavs/1.wav\n",
            "{\"text\": \"动点了小看三个问题首先那就是这一轮全球经动荡的表现\", \"timestamps\": [0.36, 0.52, 0.64, 0.84, 1.00, 1.16, 1.28, 1.44, 1.64, 2.40, 2.52, 2.68, 2.84, 3.04, 3.28, 3.36, 3.52, 3.76, 3.92, 4.04, 4.12, 4.36, 4.52, 4.72, 4.88], \"tokens\":[\"动\", \"点\", \"了\", \"小\", \"看\", \"三\", \"个\", \"问\", \"题\", \"首\", \"先\", \"那\", \"就\", \"是\", \"这\", \"一\", \"轮\", \"全\", \"球\", \"经\", \"动\", \"荡\", \"的\", \"表\", \"现\"]}\n",
            "----\n",
            "./sherpa-onnx-zh-wenet-aishell/test_wavs/8k.wav\n",
            "{\"text\": \"深度的分需对于和全球金融动荡背忘地根远\", \"timestamps\": [0.60, 0.76, 0.92, 1.08, 1.44, 1.84, 2.00, 2.28, 2.80, 3.00, 3.12, 3.24, 3.40, 3.56, 3.68, 3.80, 3.92, 4.08, 4.28], \"tokens\":[\"深\", \"度\", \"的\", \"分\", \"需\", \"对\", \"于\", \"和\", \"全\", \"球\", \"金\", \"融\", \"动\", \"荡\", \"背\", \"忘\", \"地\", \"根\", \"远\"]}\n",
            "----\n",
            "num threads: 2\n",
            "decoding method: greedy_search\n",
            "Elapsed seconds: 0.629 s\n",
            "Real time factor (RTF): 0.629 / 15.289 = 0.041\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# sherpa-onnx-zh-wenet-aishell2"
      ],
      "metadata": {
        "id": "PF2o5sriLo8I"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "git lfs install\n",
        "git clone https://huggingface.co/csukuangfj/sherpa-onnx-zh-wenet-aishell2\n",
        "ls -lh sherpa-onnx-zh-wenet-aishell2"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5G_vUyWULy8T",
        "outputId": "0d38b047-7fbc-44d6-c9e8-20f0b2c9ab22"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Git LFS initialized.\n",
            "Cloning into 'sherpa-onnx-zh-wenet-aishell2'...\n",
            "remote: Enumerating objects: 24, done.\u001b[K\n",
            "remote: Counting objects: 100% (21/21), done.\u001b[K\n",
            "remote: Compressing objects: 100% (20/20), done.\u001b[K\n",
            "remote: Total 24 (delta 1), reused 0 (delta 0), pack-reused 3\u001b[K\n",
            "Unpacking objects: 100% (24/24), 366.07 KiB | 5.30 MiB/s, done.\n",
            "Filtering content: 100% (4/4), 371.28 MiB | 58.86 MiB/s, done.\n",
            "total 372M\n",
            "-rw-r--r-- 1 root root  48M Nov 16 03:50 model.int8.onnx\n",
            "-rw-r--r-- 1 root root 139M Nov 16 03:51 model.onnx\n",
            "-rw-r--r-- 1 root root  48M Nov 16 03:50 model-streaming.int8.onnx\n",
            "-rw-r--r-- 1 root root 138M Nov 16 03:51 model-streaming.onnx\n",
            "-rw-r--r-- 1 root root  131 Nov 16 03:50 README.md\n",
            "drwxr-xr-x 2 root root 4.0K Nov 16 03:50 test_wavs\n",
            "-rwxr-xr-x 1 root root  45K Nov 16 03:50 tokens.txt\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Streaming decoding"
      ],
      "metadata": {
        "id": "KJgMaMMLLuAQ"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# float32 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-zh-wenet-aishell2/model-streaming.onnx \\\n",
        "  --tokens=./sherpa-onnx-zh-wenet-aishell2/tokens.txt \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell2/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell2/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell2/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uTDL8ah1L6Hv",
        "outputId": "faee69e2-96ab-42e0-dc89-6f5a2f4d821a"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx --wenet-ctc-model=./sherpa-onnx-zh-wenet-aishell2/model-streaming.onnx --tokens=./sherpa-onnx-zh-wenet-aishell2/tokens.txt ./sherpa-onnx-zh-wenet-aishell2/test_wavs/0.wav ./sherpa-onnx-zh-wenet-aishell2/test_wavs/1.wav ./sherpa-onnx-zh-wenet-aishell2/test_wavs/8k.wav \n",
            "\n",
            "OnlineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OnlineModelConfig(transducer=OnlineTransducerModelConfig(encoder=\"\", decoder=\"\", joiner=\"\"), paraformer=OnlineParaformerModelConfig(encoder=\"\", decoder=\"\"), wenet_ctc=OnlineWenetCtcModelConfig(model=\"./sherpa-onnx-zh-wenet-aishell2/model-streaming.onnx\", chunk_size=16, num_left_chunks=4), tokens=\"./sherpa-onnx-zh-wenet-aishell2/tokens.txt\", num_threads=1, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OnlineLMConfig(model=\"\", scale=0.5), endpoint_config=EndpointConfig(rule1=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=2.4, min_utterance_length=0), rule2=EndpointRule(must_contain_nonsilence=True, min_trailing_silence=1.2, min_utterance_length=0), rule3=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=0, min_utterance_length=20)), enable_endpoint=True, max_active_paths=4, hotwords_score=1.5, hotwords_file=\"\", decoding_method=\"greedy_search\")\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/features.cc:AcceptWaveformImpl:85 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "./sherpa-onnx-zh-wenet-aishell2/test_wavs/0.wav\n",
            "Elapsed seconds: 1.1, Real time factor (RTF): 0.2\n",
            "对我做了介绍妈我想做的事玩家如果对我研究感兴趣\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"对我做了介绍妈我想做的事玩家如果对我研究感兴趣\", \"timestamps\": [0.00, 0.08, 0.24, 0.36, 0.52, 0.04, 0.24, 0.48, 0.60, 0.08, 0.20, 0.32, 0.32, 0.44, 0.60, 0.08, 0.16, 0.24, 0.40, 0.56, 0.04, 0.24, 0.44], \"tokens\":[\"对\", \"我\", \"做\", \"了\", \"介\", \"绍\", \"妈\", \"我\", \"想\", \"做\", \"的\", \"事\", \"玩\", \"家\", \"如\", \"果\", \"对\", \"我\", \"研\", \"究\", \"感\", \"兴\", \"趣\"]}\n",
            "\n",
            "./sherpa-onnx-zh-wenet-aishell2/test_wavs/1.wav\n",
            "Elapsed seconds: 1.1, Real time factor (RTF): 0.22\n",
            "重点的想看三个问题首先那就是在一轮全球金融动荡的表现\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"重点的想看三个问题首先那就是在一轮全球金融动荡的表现\", \"timestamps\": [0.40, 0.56, 0.08, 0.20, 0.40, 0.56, 0.04, 0.20, 0.36, 0.52, 0.04, 0.16, 0.32, 0.48, 0.12, 0.24, 0.40, 0.00, 0.08, 0.24, 0.36, 0.48, 0.60, 0.08, 0.24, 0.48], \"tokens\":[\"重\", \"点\", \"的\", \"想\", \"看\", \"三\", \"个\", \"问\", \"题\", \"首\", \"先\", \"那\", \"就\", \"是\", \"在\", \"一\", \"轮\", \"全\", \"球\", \"金\", \"融\", \"动\", \"荡\", \"的\", \"表\", \"现\"]}\n",
            "\n",
            "./sherpa-onnx-zh-wenet-aishell2/test_wavs/8k.wav\n",
            "Elapsed seconds: 1.1, Real time factor (RTF): 0.23\n",
            "深度的分析析再一次全球金融动荡背后的根源\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"深度的分析析再一次全球金融动荡背后的根源\", \"timestamps\": [0.04, 0.20, 0.32, 0.44, 0.60, 0.16, 0.00, 0.16, 0.36, 0.28, 0.44, 0.00, 0.12, 0.24, 0.40, 0.52, 0.04, 0.12, 0.28, 0.44], \"tokens\":[\"深\", \"度\", \"的\", \"分\", \"析\", \"析\", \"再\", \"一\", \"次\", \"全\", \"球\", \"金\", \"融\", \"动\", \"荡\", \"背\", \"后\", \"的\", \"根\", \"源\"]}\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# int8 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-zh-wenet-aishell2/model-streaming.int8.onnx \\\n",
        "  --tokens=./sherpa-onnx-zh-wenet-aishell2/tokens.txt \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell2/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell2/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell2/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "p98WSninL_xn",
        "outputId": "8b467c06-f8e2-47c3-881f-9be7ffa5badc"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx --wenet-ctc-model=./sherpa-onnx-zh-wenet-aishell2/model-streaming.int8.onnx --tokens=./sherpa-onnx-zh-wenet-aishell2/tokens.txt ./sherpa-onnx-zh-wenet-aishell2/test_wavs/0.wav ./sherpa-onnx-zh-wenet-aishell2/test_wavs/1.wav ./sherpa-onnx-zh-wenet-aishell2/test_wavs/8k.wav \n",
            "\n",
            "OnlineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OnlineModelConfig(transducer=OnlineTransducerModelConfig(encoder=\"\", decoder=\"\", joiner=\"\"), paraformer=OnlineParaformerModelConfig(encoder=\"\", decoder=\"\"), wenet_ctc=OnlineWenetCtcModelConfig(model=\"./sherpa-onnx-zh-wenet-aishell2/model-streaming.int8.onnx\", chunk_size=16, num_left_chunks=4), tokens=\"./sherpa-onnx-zh-wenet-aishell2/tokens.txt\", num_threads=1, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OnlineLMConfig(model=\"\", scale=0.5), endpoint_config=EndpointConfig(rule1=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=2.4, min_utterance_length=0), rule2=EndpointRule(must_contain_nonsilence=True, min_trailing_silence=1.2, min_utterance_length=0), rule3=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=0, min_utterance_length=20)), enable_endpoint=True, max_active_paths=4, hotwords_score=1.5, hotwords_file=\"\", decoding_method=\"greedy_search\")\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/features.cc:AcceptWaveformImpl:85 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "./sherpa-onnx-zh-wenet-aishell2/test_wavs/0.wav\n",
            "Elapsed seconds: 0.9, Real time factor (RTF): 0.16\n",
            "对我做了介绍妈我想做的事玩家如果对我研究感兴趣\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"对我做了介绍妈我想做的事玩家如果对我研究感兴趣\", \"timestamps\": [0.00, 0.08, 0.24, 0.36, 0.52, 0.04, 0.24, 0.48, 0.60, 0.08, 0.20, 0.32, 0.32, 0.44, 0.60, 0.08, 0.16, 0.24, 0.40, 0.56, 0.04, 0.24, 0.44], \"tokens\":[\"对\", \"我\", \"做\", \"了\", \"介\", \"绍\", \"妈\", \"我\", \"想\", \"做\", \"的\", \"事\", \"玩\", \"家\", \"如\", \"果\", \"对\", \"我\", \"研\", \"究\", \"感\", \"兴\", \"趣\"]}\n",
            "\n",
            "./sherpa-onnx-zh-wenet-aishell2/test_wavs/1.wav\n",
            "Elapsed seconds: 0.9, Real time factor (RTF): 0.18\n",
            "重点的想看三个问题首先那就是在一轮全球金动动荡的表现\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"重点的想看三个问题首先那就是在一轮全球金动动荡的表现\", \"timestamps\": [0.40, 0.56, 0.08, 0.20, 0.40, 0.56, 0.04, 0.20, 0.36, 0.52, 0.04, 0.16, 0.32, 0.48, 0.12, 0.24, 0.40, 0.00, 0.08, 0.24, 0.36, 0.48, 0.60, 0.08, 0.24, 0.48], \"tokens\":[\"重\", \"点\", \"的\", \"想\", \"看\", \"三\", \"个\", \"问\", \"题\", \"首\", \"先\", \"那\", \"就\", \"是\", \"在\", \"一\", \"轮\", \"全\", \"球\", \"金\", \"动\", \"动\", \"荡\", \"的\", \"表\", \"现\"]}\n",
            "\n",
            "./sherpa-onnx-zh-wenet-aishell2/test_wavs/8k.wav\n",
            "Elapsed seconds: 0.84, Real time factor (RTF): 0.18\n",
            "深度的分析析再一次全球金融动荡背后的根源\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"深度的分析析再一次全球金融动荡背后的根源\", \"timestamps\": [0.04, 0.20, 0.32, 0.44, 0.60, 0.16, 0.00, 0.16, 0.36, 0.28, 0.44, 0.00, 0.12, 0.24, 0.40, 0.52, 0.04, 0.12, 0.28, 0.44], \"tokens\":[\"深\", \"度\", \"的\", \"分\", \"析\", \"析\", \"再\", \"一\", \"次\", \"全\", \"球\", \"金\", \"融\", \"动\", \"荡\", \"背\", \"后\", \"的\", \"根\", \"源\"]}\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Non-streaming decoding"
      ],
      "metadata": {
        "id": "_M6BVQ5jLwLr"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# float32 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx-offline \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-zh-wenet-aishell2/model.onnx \\\n",
        "  --tokens=./sherpa-onnx-zh-wenet-aishell2/tokens.txt \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell2/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell2/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell2/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UlghU-YSL9eh",
        "outputId": "f9fac33c-1049-465f-aad4-b2b88d4b1a5e"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx-offline --wenet-ctc-model=./sherpa-onnx-zh-wenet-aishell2/model.onnx --tokens=./sherpa-onnx-zh-wenet-aishell2/tokens.txt ./sherpa-onnx-zh-wenet-aishell2/test_wavs/0.wav ./sherpa-onnx-zh-wenet-aishell2/test_wavs/1.wav ./sherpa-onnx-zh-wenet-aishell2/test_wavs/8k.wav \n",
            "\n",
            "OfflineRecognizerConfig(feat_config=OfflineFeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename=\"\", decoder_filename=\"\", joiner_filename=\"\"), paraformer=OfflineParaformerModelConfig(model=\"\"), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=\"\"), whisper=OfflineWhisperModelConfig(encoder=\"\", decoder=\"\", language=\"\", task=\"transcribe\"), tdnn=OfflineTdnnModelConfig(model=\"\"), zipformer_ctc=OfflineZipformerCtcModelConfig(model=\"\"), wenet_ctc=OfflineWenetCtcModelConfig(model=\"./sherpa-onnx-zh-wenet-aishell2/model.onnx\"), tokens=\"./sherpa-onnx-zh-wenet-aishell2/tokens.txt\", num_threads=2, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OfflineLMConfig(model=\"\", scale=0.5), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph=\"\", max_active=3000), decoding_method=\"greedy_search\", max_active_paths=4, hotwords_file=\"\", hotwords_score=1.5)\n",
            "Creating recognizer ...\n",
            "Started\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/offline-stream.cc:AcceptWaveformImpl:113 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "Done!\n",
            "\n",
            "./sherpa-onnx-zh-wenet-aishell2/test_wavs/0.wav\n",
            "{\"text\": \"对我做了介绍往我想做算是玩家如果对我的研究感兴趣呢\", \"timestamps\": [0.56, 0.72, 0.88, 1.00, 1.16, 1.36, 2.16, 2.40, 2.52, 2.64, 2.76, 2.88, 3.52, 3.64, 3.80, 3.92, 4.00, 4.08, 4.16, 4.24, 4.40, 4.52, 4.72, 4.92, 5.08], \"tokens\":[\"对\", \"我\", \"做\", \"了\", \"介\", \"绍\", \"往\", \"我\", \"想\", \"做\", \"算\", \"是\", \"玩\", \"家\", \"如\", \"果\", \"对\", \"我\", \"的\", \"研\", \"究\", \"感\", \"兴\", \"趣\", \"呢\"]}\n",
            "----\n",
            "./sherpa-onnx-zh-wenet-aishell2/test_wavs/1.wav\n",
            "{\"text\": \"重点来想看三个问题首先那就是在一轮全球金动荡的表现\", \"timestamps\": [0.40, 0.56, 0.72, 0.84, 1.04, 1.20, 1.32, 1.48, 1.64, 2.44, 2.60, 2.72, 2.88, 3.04, 3.32, 3.44, 3.56, 3.80, 3.92, 4.08, 4.20, 4.44, 4.56, 4.72, 4.92], \"tokens\":[\"重\", \"点\", \"来\", \"想\", \"看\", \"三\", \"个\", \"问\", \"题\", \"首\", \"先\", \"那\", \"就\", \"是\", \"在\", \"一\", \"轮\", \"全\", \"球\", \"金\", \"动\", \"荡\", \"的\", \"表\", \"现\"]}\n",
            "----\n",
            "./sherpa-onnx-zh-wenet-aishell2/test_wavs/8k.wav\n",
            "{\"text\": \"深度的分析师对一次全球金融动荡背后的根源\", \"timestamps\": [0.64, 0.80, 0.96, 1.08, 1.24, 1.44, 1.88, 2.04, 2.28, 2.84, 3.00, 3.16, 3.32, 3.44, 3.60, 3.72, 3.88, 3.96, 4.12, 4.28], \"tokens\":[\"深\", \"度\", \"的\", \"分\", \"析\", \"师\", \"对\", \"一\", \"次\", \"全\", \"球\", \"金\", \"融\", \"动\", \"荡\", \"背\", \"后\", \"的\", \"根\", \"源\"]}\n",
            "----\n",
            "num threads: 2\n",
            "decoding method: greedy_search\n",
            "Elapsed seconds: 1.685 s\n",
            "Real time factor (RTF): 1.685 / 15.289 = 0.110\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# int8 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx-offline \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-zh-wenet-aishell2/model.int8.onnx \\\n",
        "  --tokens=./sherpa-onnx-zh-wenet-aishell2/tokens.txt \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell2/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell2/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-aishell2/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nrlJD3DXMFXN",
        "outputId": "e05f1f3f-3edb-4e3d-9f69-cee4b1865664"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx-offline --wenet-ctc-model=./sherpa-onnx-zh-wenet-aishell2/model.int8.onnx --tokens=./sherpa-onnx-zh-wenet-aishell2/tokens.txt ./sherpa-onnx-zh-wenet-aishell2/test_wavs/0.wav ./sherpa-onnx-zh-wenet-aishell2/test_wavs/1.wav ./sherpa-onnx-zh-wenet-aishell2/test_wavs/8k.wav \n",
            "\n",
            "OfflineRecognizerConfig(feat_config=OfflineFeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename=\"\", decoder_filename=\"\", joiner_filename=\"\"), paraformer=OfflineParaformerModelConfig(model=\"\"), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=\"\"), whisper=OfflineWhisperModelConfig(encoder=\"\", decoder=\"\", language=\"\", task=\"transcribe\"), tdnn=OfflineTdnnModelConfig(model=\"\"), zipformer_ctc=OfflineZipformerCtcModelConfig(model=\"\"), wenet_ctc=OfflineWenetCtcModelConfig(model=\"./sherpa-onnx-zh-wenet-aishell2/model.int8.onnx\"), tokens=\"./sherpa-onnx-zh-wenet-aishell2/tokens.txt\", num_threads=2, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OfflineLMConfig(model=\"\", scale=0.5), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph=\"\", max_active=3000), decoding_method=\"greedy_search\", max_active_paths=4, hotwords_file=\"\", hotwords_score=1.5)\n",
            "Creating recognizer ...\n",
            "Started\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/offline-stream.cc:AcceptWaveformImpl:113 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "Done!\n",
            "\n",
            "./sherpa-onnx-zh-wenet-aishell2/test_wavs/0.wav\n",
            "{\"text\": \"对我做了介绍往我想说算是玩家如果对我的研究感兴趣呢\", \"timestamps\": [0.56, 0.72, 0.88, 1.00, 1.16, 1.36, 2.16, 2.40, 2.52, 2.64, 2.76, 2.88, 3.52, 3.64, 3.80, 3.92, 4.00, 4.12, 4.16, 4.28, 4.40, 4.52, 4.72, 4.92, 5.08], \"tokens\":[\"对\", \"我\", \"做\", \"了\", \"介\", \"绍\", \"往\", \"我\", \"想\", \"说\", \"算\", \"是\", \"玩\", \"家\", \"如\", \"果\", \"对\", \"我\", \"的\", \"研\", \"究\", \"感\", \"兴\", \"趣\", \"呢\"]}\n",
            "----\n",
            "./sherpa-onnx-zh-wenet-aishell2/test_wavs/1.wav\n",
            "{\"text\": \"重点来想看三个问题首先那就是在一轮全球金动荡的表现\", \"timestamps\": [0.40, 0.56, 0.72, 0.84, 1.04, 1.20, 1.32, 1.48, 1.64, 2.44, 2.60, 2.72, 2.88, 3.04, 3.32, 3.44, 3.56, 3.80, 3.92, 4.08, 4.20, 4.44, 4.56, 4.72, 4.92], \"tokens\":[\"重\", \"点\", \"来\", \"想\", \"看\", \"三\", \"个\", \"问\", \"题\", \"首\", \"先\", \"那\", \"就\", \"是\", \"在\", \"一\", \"轮\", \"全\", \"球\", \"金\", \"动\", \"荡\", \"的\", \"表\", \"现\"]}\n",
            "----\n",
            "./sherpa-onnx-zh-wenet-aishell2/test_wavs/8k.wav\n",
            "{\"text\": \"深度的分析师对一次全球金融动荡背后的根源\", \"timestamps\": [0.64, 0.80, 0.96, 1.08, 1.24, 1.44, 1.88, 2.04, 2.28, 2.84, 3.00, 3.16, 3.32, 3.44, 3.60, 3.72, 3.88, 3.96, 4.12, 4.28], \"tokens\":[\"深\", \"度\", \"的\", \"分\", \"析\", \"师\", \"对\", \"一\", \"次\", \"全\", \"球\", \"金\", \"融\", \"动\", \"荡\", \"背\", \"后\", \"的\", \"根\", \"源\"]}\n",
            "----\n",
            "num threads: 2\n",
            "decoding method: greedy_search\n",
            "Elapsed seconds: 0.618 s\n",
            "Real time factor (RTF): 0.618 / 15.289 = 0.040\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# sherpa-onnx-zh-wenet-multi-cn"
      ],
      "metadata": {
        "id": "93kii7CMLqOX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "git lfs install\n",
        "git clone https://huggingface.co/csukuangfj/sherpa-onnx-zh-wenet-multi-cn\n",
        "ls -lh sherpa-onnx-zh-wenet-multi-cn"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Cc6WVbIOMai2",
        "outputId": "f23bfe9c-0082-4919-e436-30ccf8d01d7c"
      },
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Git LFS initialized.\n",
            "Cloning into 'sherpa-onnx-zh-wenet-multi-cn'...\n",
            "remote: Enumerating objects: 24, done.\u001b[K\n",
            "remote: Counting objects: 100% (21/21), done.\u001b[K\n",
            "remote: Compressing objects: 100% (20/20), done.\u001b[K\n",
            "remote: Total 24 (delta 1), reused 0 (delta 0), pack-reused 3\u001b[K\n",
            "Unpacking objects: 100% (24/24), 393.42 KiB | 6.56 MiB/s, done.\n",
            "Filtering content: 100% (4/4), 385.79 MiB | 66.00 MiB/s, done.\n",
            "total 386M\n",
            "-rw-r--r-- 1 root root  50M Nov 16 03:51 model.int8.onnx\n",
            "-rw-r--r-- 1 root root 144M Nov 16 03:51 model.onnx\n",
            "-rw-r--r-- 1 root root  50M Nov 16 03:51 model-streaming.int8.onnx\n",
            "-rw-r--r-- 1 root root 144M Nov 16 03:51 model-streaming.onnx\n",
            "-rw-r--r-- 1 root root  134 Nov 16 03:51 README.md\n",
            "drwxr-xr-x 2 root root 4.0K Nov 16 03:51 test_wavs\n",
            "-rwxr-xr-x 1 root root 119K Nov 16 03:51 tokens.txt\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Streaming decoding"
      ],
      "metadata": {
        "id": "ekCjKVATL1Fu"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# float32 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-zh-wenet-multi-cn/model-streaming.onnx \\\n",
        "  --tokens=./sherpa-onnx-zh-wenet-multi-cn/tokens.txt \\\n",
        "  ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "22156CzZMejj",
        "outputId": "51d50482-f17f-4c8b-b8f8-d3aae00726b3"
      },
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx --wenet-ctc-model=./sherpa-onnx-zh-wenet-multi-cn/model-streaming.onnx --tokens=./sherpa-onnx-zh-wenet-multi-cn/tokens.txt ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/0.wav ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/1.wav ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/8k.wav \n",
            "\n",
            "OnlineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OnlineModelConfig(transducer=OnlineTransducerModelConfig(encoder=\"\", decoder=\"\", joiner=\"\"), paraformer=OnlineParaformerModelConfig(encoder=\"\", decoder=\"\"), wenet_ctc=OnlineWenetCtcModelConfig(model=\"./sherpa-onnx-zh-wenet-multi-cn/model-streaming.onnx\", chunk_size=16, num_left_chunks=4), tokens=\"./sherpa-onnx-zh-wenet-multi-cn/tokens.txt\", num_threads=1, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OnlineLMConfig(model=\"\", scale=0.5), endpoint_config=EndpointConfig(rule1=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=2.4, min_utterance_length=0), rule2=EndpointRule(must_contain_nonsilence=True, min_trailing_silence=1.2, min_utterance_length=0), rule3=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=0, min_utterance_length=20)), enable_endpoint=True, max_active_paths=4, hotwords_score=1.5, hotwords_file=\"\", decoding_method=\"greedy_search\")\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/features.cc:AcceptWaveformImpl:85 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "./sherpa-onnx-zh-wenet-multi-cn/test_wavs/0.wav\n",
            "Elapsed seconds: 1.2, Real time factor (RTF): 0.21\n",
            "对我做了介绍啊什么我想说的是呢大家如果对我的研究感兴趣呢\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"对我做了介绍啊什么我想说的是呢大家如果对我的研究感兴趣呢\", \"timestamps\": [0.52, 0.00, 0.16, 0.28, 0.40, 0.56, 0.20, 0.04, 0.16, 0.36, 0.48, 0.60, 0.12, 0.20, 0.32, 0.20, 0.36, 0.48, 0.60, 0.04, 0.12, 0.24, 0.28, 0.44, 0.60, 0.12, 0.32, 0.48], \"tokens\":[\"对\", \"我\", \"做\", \"了\", \"介\", \"绍\", \"啊\", \"什\", \"么\", \"我\", \"想\", \"说\", \"的\", \"是\", \"呢\", \"大\", \"家\", \"如\", \"果\", \"对\", \"我\", \"的\", \"研\", \"究\", \"感\", \"兴\", \"趣\", \"呢\"]}\n",
            "\n",
            "./sherpa-onnx-zh-wenet-multi-cn/test_wavs/1.wav\n",
            "Elapsed seconds: 1.2, Real time factor (RTF): 0.23\n",
            "重点的想看三个问题首先呢就是这一轮全球金融动荡的表现\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"重点的想看三个问题首先呢就是这一轮全球金融动荡的表现\", \"timestamps\": [0.32, 0.48, 0.00, 0.12, 0.28, 0.44, 0.56, 0.08, 0.20, 0.44, 0.60, 0.08, 0.20, 0.36, 0.00, 0.12, 0.28, 0.48, 0.00, 0.12, 0.24, 0.36, 0.44, 0.56, 0.12, 0.32], \"tokens\":[\"重\", \"点\", \"的\", \"想\", \"看\", \"三\", \"个\", \"问\", \"题\", \"首\", \"先\", \"呢\", \"就\", \"是\", \"这\", \"一\", \"轮\", \"全\", \"球\", \"金\", \"融\", \"动\", \"荡\", \"的\", \"表\", \"现\"]}\n",
            "\n",
            "./sherpa-onnx-zh-wenet-multi-cn/test_wavs/8k.wav\n",
            "Elapsed seconds: 1.1, Real time factor (RTF): 0.24\n",
            "删东的分析析这一次全球金融动荡背后的根源\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"删东的分析析这一次全球金融动荡背后的根源\", \"timestamps\": [0.00, 0.08, 0.20, 0.36, 0.48, 0.00, 0.52, 0.04, 0.24, 0.20, 0.36, 0.52, 0.00, 0.16, 0.28, 0.44, 0.56, 0.04, 0.16, 0.36], \"tokens\":[\"删\", \"东\", \"的\", \"分\", \"析\", \"析\", \"这\", \"一\", \"次\", \"全\", \"球\", \"金\", \"融\", \"动\", \"荡\", \"背\", \"后\", \"的\", \"根\", \"源\"]}\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# int8 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-zh-wenet-multi-cn/model-streaming.int8.onnx \\\n",
        "  --tokens=./sherpa-onnx-zh-wenet-multi-cn/tokens.txt \\\n",
        "  ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TwY6UTorMkZp",
        "outputId": "006c79d0-b423-4cac-98d2-eea57e9630fb"
      },
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx --wenet-ctc-model=./sherpa-onnx-zh-wenet-multi-cn/model-streaming.int8.onnx --tokens=./sherpa-onnx-zh-wenet-multi-cn/tokens.txt ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/0.wav ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/1.wav ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/8k.wav \n",
            "\n",
            "OnlineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OnlineModelConfig(transducer=OnlineTransducerModelConfig(encoder=\"\", decoder=\"\", joiner=\"\"), paraformer=OnlineParaformerModelConfig(encoder=\"\", decoder=\"\"), wenet_ctc=OnlineWenetCtcModelConfig(model=\"./sherpa-onnx-zh-wenet-multi-cn/model-streaming.int8.onnx\", chunk_size=16, num_left_chunks=4), tokens=\"./sherpa-onnx-zh-wenet-multi-cn/tokens.txt\", num_threads=1, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OnlineLMConfig(model=\"\", scale=0.5), endpoint_config=EndpointConfig(rule1=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=2.4, min_utterance_length=0), rule2=EndpointRule(must_contain_nonsilence=True, min_trailing_silence=1.2, min_utterance_length=0), rule3=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=0, min_utterance_length=20)), enable_endpoint=True, max_active_paths=4, hotwords_score=1.5, hotwords_file=\"\", decoding_method=\"greedy_search\")\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/features.cc:AcceptWaveformImpl:85 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "./sherpa-onnx-zh-wenet-multi-cn/test_wavs/0.wav\n",
            "Elapsed seconds: 0.91, Real time factor (RTF): 0.16\n",
            "对我做了介绍唉什么我想说的是呢大家如果对我的研究感兴趣呢\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"对我做了介绍唉什么我想说的是呢大家如果对我的研究感兴趣呢\", \"timestamps\": [0.52, 0.00, 0.16, 0.28, 0.40, 0.56, 0.20, 0.04, 0.16, 0.36, 0.48, 0.60, 0.12, 0.20, 0.32, 0.20, 0.36, 0.48, 0.60, 0.04, 0.12, 0.24, 0.28, 0.44, 0.60, 0.12, 0.32, 0.48], \"tokens\":[\"对\", \"我\", \"做\", \"了\", \"介\", \"绍\", \"唉\", \"什\", \"么\", \"我\", \"想\", \"说\", \"的\", \"是\", \"呢\", \"大\", \"家\", \"如\", \"果\", \"对\", \"我\", \"的\", \"研\", \"究\", \"感\", \"兴\", \"趣\", \"呢\"]}\n",
            "\n",
            "./sherpa-onnx-zh-wenet-multi-cn/test_wavs/1.wav\n",
            "Elapsed seconds: 0.91, Real time factor (RTF): 0.18\n",
            "重点的想看三个问题首先呢就是这一轮全球金融动荡的表现\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"重点的想看三个问题首先呢就是这一轮全球金融动荡的表现\", \"timestamps\": [0.32, 0.48, 0.00, 0.12, 0.28, 0.44, 0.56, 0.08, 0.20, 0.44, 0.60, 0.08, 0.20, 0.36, 0.00, 0.12, 0.28, 0.48, 0.00, 0.12, 0.24, 0.36, 0.44, 0.56, 0.12, 0.32], \"tokens\":[\"重\", \"点\", \"的\", \"想\", \"看\", \"三\", \"个\", \"问\", \"题\", \"首\", \"先\", \"呢\", \"就\", \"是\", \"这\", \"一\", \"轮\", \"全\", \"球\", \"金\", \"融\", \"动\", \"荡\", \"的\", \"表\", \"现\"]}\n",
            "\n",
            "./sherpa-onnx-zh-wenet-multi-cn/test_wavs/8k.wav\n",
            "Elapsed seconds: 0.84, Real time factor (RTF): 0.19\n",
            "删东的分析析这一次全球金融动荡背后的根源\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"删东的分析析这一次全球金融动荡背后的根源\", \"timestamps\": [0.00, 0.08, 0.20, 0.36, 0.48, 0.00, 0.52, 0.04, 0.24, 0.20, 0.36, 0.52, 0.00, 0.16, 0.28, 0.44, 0.56, 0.04, 0.16, 0.36], \"tokens\":[\"删\", \"东\", \"的\", \"分\", \"析\", \"析\", \"这\", \"一\", \"次\", \"全\", \"球\", \"金\", \"融\", \"动\", \"荡\", \"背\", \"后\", \"的\", \"根\", \"源\"]}\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Non-streaming decoding"
      ],
      "metadata": {
        "id": "NXoAhtCtMnV1"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# float32 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx-offline \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-zh-wenet-multi-cn/model.onnx \\\n",
        "  --tokens=./sherpa-onnx-zh-wenet-multi-cn/tokens.txt \\\n",
        "  ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LGtFm-3YMp6g",
        "outputId": "5c20c8b1-632e-495c-e5b4-de3a0a919000"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx-offline --wenet-ctc-model=./sherpa-onnx-zh-wenet-multi-cn/model.onnx --tokens=./sherpa-onnx-zh-wenet-multi-cn/tokens.txt ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/0.wav ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/1.wav ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/8k.wav \n",
            "\n",
            "OfflineRecognizerConfig(feat_config=OfflineFeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename=\"\", decoder_filename=\"\", joiner_filename=\"\"), paraformer=OfflineParaformerModelConfig(model=\"\"), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=\"\"), whisper=OfflineWhisperModelConfig(encoder=\"\", decoder=\"\", language=\"\", task=\"transcribe\"), tdnn=OfflineTdnnModelConfig(model=\"\"), zipformer_ctc=OfflineZipformerCtcModelConfig(model=\"\"), wenet_ctc=OfflineWenetCtcModelConfig(model=\"./sherpa-onnx-zh-wenet-multi-cn/model.onnx\"), tokens=\"./sherpa-onnx-zh-wenet-multi-cn/tokens.txt\", num_threads=2, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OfflineLMConfig(model=\"\", scale=0.5), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph=\"\", max_active=3000), decoding_method=\"greedy_search\", max_active_paths=4, hotwords_file=\"\", hotwords_score=1.5)\n",
            "Creating recognizer ...\n",
            "Started\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/offline-stream.cc:AcceptWaveformImpl:113 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "Done!\n",
            "\n",
            "./sherpa-onnx-zh-wenet-multi-cn/test_wavs/0.wav\n",
            "{\"text\": \"对我做了介绍哈什么我想说的是呢大家如果对我的研究感兴趣呢\", \"timestamps\": [0.48, 0.64, 0.80, 0.92, 1.04, 1.20, 1.48, 1.96, 2.08, 2.28, 2.40, 2.52, 2.68, 2.76, 2.92, 3.40, 3.56, 3.68, 3.80, 3.92, 4.00, 4.08, 4.16, 4.28, 4.40, 4.60, 4.80, 4.96], \"tokens\":[\"对\", \"我\", \"做\", \"了\", \"介\", \"绍\", \"哈\", \"什\", \"么\", \"我\", \"想\", \"说\", \"的\", \"是\", \"呢\", \"大\", \"家\", \"如\", \"果\", \"对\", \"我\", \"的\", \"研\", \"究\", \"感\", \"兴\", \"趣\", \"呢\"]}\n",
            "----\n",
            "./sherpa-onnx-zh-wenet-multi-cn/test_wavs/1.wav\n",
            "{\"text\": \"重点的想看三个问题首先呢就是这一轮全球进融动荡的表现\", \"timestamps\": [0.32, 0.48, 0.60, 0.76, 0.92, 1.08, 1.20, 1.36, 1.52, 2.32, 2.48, 2.64, 2.76, 2.92, 3.20, 3.32, 3.44, 3.68, 3.84, 3.96, 4.08, 4.20, 4.32, 4.44, 4.60, 4.80], \"tokens\":[\"重\", \"点\", \"的\", \"想\", \"看\", \"三\", \"个\", \"问\", \"题\", \"首\", \"先\", \"呢\", \"就\", \"是\", \"这\", \"一\", \"轮\", \"全\", \"球\", \"进\", \"融\", \"动\", \"荡\", \"的\", \"表\", \"现\"]}\n",
            "----\n",
            "./sherpa-onnx-zh-wenet-multi-cn/test_wavs/8k.wav\n",
            "{\"text\": \"深猪的分析师这一次全球金融动荡背后的根源\", \"timestamps\": [0.56, 0.72, 0.84, 1.00, 1.12, 1.32, 1.80, 1.96, 2.12, 2.72, 2.92, 3.08, 3.20, 3.36, 3.48, 3.64, 3.76, 3.88, 4.00, 4.20], \"tokens\":[\"深\", \"猪\", \"的\", \"分\", \"析\", \"师\", \"这\", \"一\", \"次\", \"全\", \"球\", \"金\", \"融\", \"动\", \"荡\", \"背\", \"后\", \"的\", \"根\", \"源\"]}\n",
            "----\n",
            "num threads: 2\n",
            "decoding method: greedy_search\n",
            "Elapsed seconds: 1.996 s\n",
            "Real time factor (RTF): 1.996 / 15.289 = 0.131\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# int8 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx-offline \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-zh-wenet-multi-cn/model.int8.onnx \\\n",
        "  --tokens=./sherpa-onnx-zh-wenet-multi-cn/tokens.txt \\\n",
        "  ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pp39zoI_MsVh",
        "outputId": "0fad3cb5-abee-455b-f390-a7da25bb6123"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx-offline --wenet-ctc-model=./sherpa-onnx-zh-wenet-multi-cn/model.int8.onnx --tokens=./sherpa-onnx-zh-wenet-multi-cn/tokens.txt ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/0.wav ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/1.wav ./sherpa-onnx-zh-wenet-multi-cn/test_wavs/8k.wav \n",
            "\n",
            "OfflineRecognizerConfig(feat_config=OfflineFeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename=\"\", decoder_filename=\"\", joiner_filename=\"\"), paraformer=OfflineParaformerModelConfig(model=\"\"), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=\"\"), whisper=OfflineWhisperModelConfig(encoder=\"\", decoder=\"\", language=\"\", task=\"transcribe\"), tdnn=OfflineTdnnModelConfig(model=\"\"), zipformer_ctc=OfflineZipformerCtcModelConfig(model=\"\"), wenet_ctc=OfflineWenetCtcModelConfig(model=\"./sherpa-onnx-zh-wenet-multi-cn/model.int8.onnx\"), tokens=\"./sherpa-onnx-zh-wenet-multi-cn/tokens.txt\", num_threads=2, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OfflineLMConfig(model=\"\", scale=0.5), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph=\"\", max_active=3000), decoding_method=\"greedy_search\", max_active_paths=4, hotwords_file=\"\", hotwords_score=1.5)\n",
            "Creating recognizer ...\n",
            "Started\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/offline-stream.cc:AcceptWaveformImpl:113 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "Done!\n",
            "\n",
            "./sherpa-onnx-zh-wenet-multi-cn/test_wavs/0.wav\n",
            "{\"text\": \"对我做了介绍哈什么我想说的是呢大家如果对我的研究感兴趣呢\", \"timestamps\": [0.48, 0.64, 0.80, 0.92, 1.04, 1.24, 1.48, 1.96, 2.08, 2.28, 2.40, 2.52, 2.68, 2.76, 2.92, 3.40, 3.56, 3.68, 3.80, 3.88, 4.00, 4.08, 4.16, 4.28, 4.40, 4.60, 4.80, 4.96], \"tokens\":[\"对\", \"我\", \"做\", \"了\", \"介\", \"绍\", \"哈\", \"什\", \"么\", \"我\", \"想\", \"说\", \"的\", \"是\", \"呢\", \"大\", \"家\", \"如\", \"果\", \"对\", \"我\", \"的\", \"研\", \"究\", \"感\", \"兴\", \"趣\", \"呢\"]}\n",
            "----\n",
            "./sherpa-onnx-zh-wenet-multi-cn/test_wavs/1.wav\n",
            "{\"text\": \"重点的想看三个问题首先呢就是这一轮全球进融动荡的表现\", \"timestamps\": [0.32, 0.48, 0.60, 0.76, 0.92, 1.08, 1.20, 1.36, 1.52, 2.32, 2.48, 2.64, 2.76, 2.92, 3.20, 3.32, 3.44, 3.68, 3.84, 3.96, 4.08, 4.20, 4.32, 4.44, 4.60, 4.80], \"tokens\":[\"重\", \"点\", \"的\", \"想\", \"看\", \"三\", \"个\", \"问\", \"题\", \"首\", \"先\", \"呢\", \"就\", \"是\", \"这\", \"一\", \"轮\", \"全\", \"球\", \"进\", \"融\", \"动\", \"荡\", \"的\", \"表\", \"现\"]}\n",
            "----\n",
            "./sherpa-onnx-zh-wenet-multi-cn/test_wavs/8k.wav\n",
            "{\"text\": \"深猪的分析师这一次全球金融动荡背后的根源\", \"timestamps\": [0.56, 0.72, 0.84, 1.00, 1.12, 1.32, 1.80, 1.96, 2.12, 2.72, 2.92, 3.08, 3.20, 3.36, 3.48, 3.64, 3.76, 3.88, 4.00, 4.20], \"tokens\":[\"深\", \"猪\", \"的\", \"分\", \"析\", \"师\", \"这\", \"一\", \"次\", \"全\", \"球\", \"金\", \"融\", \"动\", \"荡\", \"背\", \"后\", \"的\", \"根\", \"源\"]}\n",
            "----\n",
            "num threads: 2\n",
            "decoding method: greedy_search\n",
            "Elapsed seconds: 0.659 s\n",
            "Real time factor (RTF): 0.659 / 15.289 = 0.043\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# sherpa-onnx-zh-wenet-wenetspeech"
      ],
      "metadata": {
        "id": "xQg4P_SmLryX"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "git lfs install\n",
        "git clone https://huggingface.co/csukuangfj/sherpa-onnx-zh-wenet-wenetspeech\n",
        "ls -lh sherpa-onnx-zh-wenet-wenetspeech"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_Z2AyeqdMzw3",
        "outputId": "3eabce85-174e-464c-a07e-8d1db75f99ff"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Git LFS initialized.\n",
            "Cloning into 'sherpa-onnx-zh-wenet-wenetspeech'...\n",
            "remote: Enumerating objects: 24, done.\u001b[K\n",
            "remote: Counting objects: 100% (21/21), done.\u001b[K\n",
            "remote: Compressing objects: 100% (20/20), done.\u001b[K\n",
            "remote: Total 24 (delta 1), reused 0 (delta 0), pack-reused 3\u001b[K\n",
            "Unpacking objects: 100% (24/24), 367.04 KiB | 5.40 MiB/s, done.\n",
            "Filtering content: 100% (4/4), 930.41 MiB | 54.44 MiB/s, done.\n",
            "total 931M\n",
            "-rw-r--r-- 1 root root 128M Nov 16 03:51 model.int8.onnx\n",
            "-rw-r--r-- 1 root root 339M Nov 16 03:52 model.onnx\n",
            "-rw-r--r-- 1 root root 127M Nov 16 03:52 model-streaming.int8.onnx\n",
            "-rw-r--r-- 1 root root 339M Nov 16 03:52 model-streaming.onnx\n",
            "-rw-r--r-- 1 root root  134 Nov 16 03:51 README.md\n",
            "drwxr-xr-x 2 root root 4.0K Nov 16 03:51 test_wavs\n",
            "-rwxr-xr-x 1 root root  48K Nov 16 03:51 tokens.txt\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Streaming decoding"
      ],
      "metadata": {
        "id": "ztg_sDfzM61a"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# float32 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-zh-wenet-wenetspeech/model-streaming.onnx \\\n",
        "  --tokens=./sherpa-onnx-zh-wenet-wenetspeech/tokens.txt \\\n",
        "  ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Gj5ccCafM-Je",
        "outputId": "789ab502-080d-46b3-8458-f9325118ce29"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx --wenet-ctc-model=./sherpa-onnx-zh-wenet-wenetspeech/model-streaming.onnx --tokens=./sherpa-onnx-zh-wenet-wenetspeech/tokens.txt ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/0.wav ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/1.wav ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/8k.wav \n",
            "\n",
            "OnlineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OnlineModelConfig(transducer=OnlineTransducerModelConfig(encoder=\"\", decoder=\"\", joiner=\"\"), paraformer=OnlineParaformerModelConfig(encoder=\"\", decoder=\"\"), wenet_ctc=OnlineWenetCtcModelConfig(model=\"./sherpa-onnx-zh-wenet-wenetspeech/model-streaming.onnx\", chunk_size=16, num_left_chunks=4), tokens=\"./sherpa-onnx-zh-wenet-wenetspeech/tokens.txt\", num_threads=1, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OnlineLMConfig(model=\"\", scale=0.5), endpoint_config=EndpointConfig(rule1=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=2.4, min_utterance_length=0), rule2=EndpointRule(must_contain_nonsilence=True, min_trailing_silence=1.2, min_utterance_length=0), rule3=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=0, min_utterance_length=20)), enable_endpoint=True, max_active_paths=4, hotwords_score=1.5, hotwords_file=\"\", decoding_method=\"greedy_search\")\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/features.cc:AcceptWaveformImpl:85 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/0.wav\n",
            "Elapsed seconds: 3.8, Real time factor (RTF): 0.69\n",
            "对我做了介绍那么我想做的是呢大家如果对我的研究感兴趣呢\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"对我做了介绍那么我想做的是呢大家如果对我的研究感兴趣呢\", \"timestamps\": [0.48, 0.00, 0.16, 0.28, 0.40, 0.56, 0.04, 0.16, 0.36, 0.48, 0.60, 0.08, 0.20, 0.36, 0.20, 0.32, 0.48, 0.56, 0.04, 0.12, 0.20, 0.32, 0.44, 0.56, 0.12, 0.28, 0.48], \"tokens\":[\"对\", \"我\", \"做\", \"了\", \"介\", \"绍\", \"那\", \"么\", \"我\", \"想\", \"做\", \"的\", \"是\", \"呢\", \"大\", \"家\", \"如\", \"果\", \"对\", \"我\", \"的\", \"研\", \"究\", \"感\", \"兴\", \"趣\", \"呢\"]}\n",
            "\n",
            "./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/1.wav\n",
            "Elapsed seconds: 3.8, Real time factor (RTF): 0.75\n",
            "重点来想谈三个问题首先呢就是这一轮全球金融动荡的表现\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"重点来想谈三个问题首先呢就是这一轮全球金融动荡的表现\", \"timestamps\": [0.32, 0.48, 0.00, 0.12, 0.28, 0.44, 0.56, 0.04, 0.16, 0.40, 0.56, 0.08, 0.20, 0.36, 0.00, 0.12, 0.24, 0.48, 0.00, 0.12, 0.24, 0.36, 0.48, 0.56, 0.12, 0.28], \"tokens\":[\"重\", \"点\", \"来\", \"想\", \"谈\", \"三\", \"个\", \"问\", \"题\", \"首\", \"先\", \"呢\", \"就\", \"是\", \"这\", \"一\", \"轮\", \"全\", \"球\", \"金\", \"融\", \"动\", \"荡\", \"的\", \"表\", \"现\"]}\n",
            "\n",
            "./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/8k.wav\n",
            "Elapsed seconds: 3.6, Real time factor (RTF): 0.8\n",
            "山柱的分析这一次全球金融动荡背后的根源\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"山柱的分析这一次全球金融动荡背后的根源\", \"timestamps\": [0.00, 0.08, 0.20, 0.36, 0.60, 0.52, 0.04, 0.20, 0.16, 0.36, 0.52, 0.00, 0.12, 0.28, 0.40, 0.52, 0.00, 0.16, 0.32], \"tokens\":[\"山\", \"柱\", \"的\", \"分\", \"析\", \"这\", \"一\", \"次\", \"全\", \"球\", \"金\", \"融\", \"动\", \"荡\", \"背\", \"后\", \"的\", \"根\", \"源\"]}\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# int8 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-zh-wenet-wenetspeech/model-streaming.int8.onnx \\\n",
        "  --tokens=./sherpa-onnx-zh-wenet-wenetspeech/tokens.txt \\\n",
        "  ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ltC0GXDqNFiI",
        "outputId": "d00072cf-e2a1-4c18-f52c-3bfec46123da"
      },
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx --wenet-ctc-model=./sherpa-onnx-zh-wenet-wenetspeech/model-streaming.int8.onnx --tokens=./sherpa-onnx-zh-wenet-wenetspeech/tokens.txt ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/0.wav ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/1.wav ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/8k.wav \n",
            "\n",
            "OnlineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OnlineModelConfig(transducer=OnlineTransducerModelConfig(encoder=\"\", decoder=\"\", joiner=\"\"), paraformer=OnlineParaformerModelConfig(encoder=\"\", decoder=\"\"), wenet_ctc=OnlineWenetCtcModelConfig(model=\"./sherpa-onnx-zh-wenet-wenetspeech/model-streaming.int8.onnx\", chunk_size=16, num_left_chunks=4), tokens=\"./sherpa-onnx-zh-wenet-wenetspeech/tokens.txt\", num_threads=1, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OnlineLMConfig(model=\"\", scale=0.5), endpoint_config=EndpointConfig(rule1=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=2.4, min_utterance_length=0), rule2=EndpointRule(must_contain_nonsilence=True, min_trailing_silence=1.2, min_utterance_length=0), rule3=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=0, min_utterance_length=20)), enable_endpoint=True, max_active_paths=4, hotwords_score=1.5, hotwords_file=\"\", decoding_method=\"greedy_search\")\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/features.cc:AcceptWaveformImpl:85 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/0.wav\n",
            "Elapsed seconds: 2.8, Real time factor (RTF): 0.49\n",
            "对我做了介绍那么我想做的是呢大家如果对我的研究感兴趣呢\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"对我做了介绍那么我想做的是呢大家如果对我的研究感兴趣呢\", \"timestamps\": [0.48, 0.00, 0.16, 0.28, 0.40, 0.60, 0.04, 0.16, 0.36, 0.48, 0.00, 0.08, 0.20, 0.36, 0.20, 0.32, 0.48, 0.56, 0.04, 0.12, 0.20, 0.32, 0.44, 0.56, 0.12, 0.28, 0.48], \"tokens\":[\"对\", \"我\", \"做\", \"了\", \"介\", \"绍\", \"那\", \"么\", \"我\", \"想\", \"做\", \"的\", \"是\", \"呢\", \"大\", \"家\", \"如\", \"果\", \"对\", \"我\", \"的\", \"研\", \"究\", \"感\", \"兴\", \"趣\", \"呢\"]}\n",
            "\n",
            "./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/1.wav\n",
            "Elapsed seconds: 2.8, Real time factor (RTF): 0.54\n",
            "重点来想谈三个问题首先呢就是这一轮全球金融动荡的表现\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"重点来想谈三个问题首先呢就是这一轮全球金融动荡的表现\", \"timestamps\": [0.32, 0.48, 0.00, 0.12, 0.28, 0.44, 0.56, 0.04, 0.16, 0.40, 0.56, 0.08, 0.20, 0.36, 0.00, 0.12, 0.24, 0.48, 0.00, 0.12, 0.24, 0.36, 0.48, 0.56, 0.12, 0.28], \"tokens\":[\"重\", \"点\", \"来\", \"想\", \"谈\", \"三\", \"个\", \"问\", \"题\", \"首\", \"先\", \"呢\", \"就\", \"是\", \"这\", \"一\", \"轮\", \"全\", \"球\", \"金\", \"融\", \"动\", \"荡\", \"的\", \"表\", \"现\"]}\n",
            "\n",
            "./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/8k.wav\n",
            "Elapsed seconds: 2.5, Real time factor (RTF): 0.55\n",
            "山柱的分析这一次全球金融动荡背后的根源\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \"山柱的分析这一次全球金融动荡背后的根源\", \"timestamps\": [0.00, 0.08, 0.20, 0.36, 0.60, 0.52, 0.04, 0.20, 0.16, 0.36, 0.52, 0.00, 0.12, 0.28, 0.40, 0.52, 0.00, 0.16, 0.32], \"tokens\":[\"山\", \"柱\", \"的\", \"分\", \"析\", \"这\", \"一\", \"次\", \"全\", \"球\", \"金\", \"融\", \"动\", \"荡\", \"背\", \"后\", \"的\", \"根\", \"源\"]}\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Non-streaming decoding"
      ],
      "metadata": {
        "id": "0rDU5rU5M8EC"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# float32 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx-offline \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-zh-wenet-wenetspeech/model.onnx \\\n",
        "  --tokens=./sherpa-onnx-zh-wenet-wenetspeech/tokens.txt \\\n",
        "  ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "oc7whE6xLMmq",
        "outputId": "1de941bc-02bd-4711-bffa-a6ec97308a30"
      },
      "execution_count": 20,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx-offline --wenet-ctc-model=./sherpa-onnx-zh-wenet-wenetspeech/model.onnx --tokens=./sherpa-onnx-zh-wenet-wenetspeech/tokens.txt ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/0.wav ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/1.wav ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/8k.wav \n",
            "\n",
            "OfflineRecognizerConfig(feat_config=OfflineFeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename=\"\", decoder_filename=\"\", joiner_filename=\"\"), paraformer=OfflineParaformerModelConfig(model=\"\"), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=\"\"), whisper=OfflineWhisperModelConfig(encoder=\"\", decoder=\"\", language=\"\", task=\"transcribe\"), tdnn=OfflineTdnnModelConfig(model=\"\"), zipformer_ctc=OfflineZipformerCtcModelConfig(model=\"\"), wenet_ctc=OfflineWenetCtcModelConfig(model=\"./sherpa-onnx-zh-wenet-wenetspeech/model.onnx\"), tokens=\"./sherpa-onnx-zh-wenet-wenetspeech/tokens.txt\", num_threads=2, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OfflineLMConfig(model=\"\", scale=0.5), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph=\"\", max_active=3000), decoding_method=\"greedy_search\", max_active_paths=4, hotwords_file=\"\", hotwords_score=1.5)\n",
            "Creating recognizer ...\n",
            "Started\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/offline-stream.cc:AcceptWaveformImpl:113 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "Done!\n",
            "\n",
            "./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/0.wav\n",
            "{\"text\": \"对我做了介绍那么我想说的是大家如果对我的研究感兴趣呢\", \"timestamps\": [0.48, 0.64, 0.76, 0.88, 1.04, 1.24, 1.96, 2.08, 2.28, 2.40, 2.52, 2.64, 2.76, 3.40, 3.52, 3.68, 3.76, 3.88, 3.96, 4.04, 4.16, 4.28, 4.40, 4.60, 4.76, 4.96], \"tokens\":[\"对\", \"我\", \"做\", \"了\", \"介\", \"绍\", \"那\", \"么\", \"我\", \"想\", \"说\", \"的\", \"是\", \"大\", \"家\", \"如\", \"果\", \"对\", \"我\", \"的\", \"研\", \"究\", \"感\", \"兴\", \"趣\", \"呢\"]}\n",
            "----\n",
            "./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/1.wav\n",
            "{\"text\": \"重点来想谈三个问题首先呢就是这一轮全球金融动荡的表现\", \"timestamps\": [0.32, 0.48, 0.60, 0.76, 0.92, 1.08, 1.20, 1.36, 1.48, 2.32, 2.48, 2.64, 2.76, 2.92, 3.20, 3.32, 3.44, 3.68, 3.84, 3.96, 4.08, 4.20, 4.32, 4.44, 4.60, 4.76], \"tokens\":[\"重\", \"点\", \"来\", \"想\", \"谈\", \"三\", \"个\", \"问\", \"题\", \"首\", \"先\", \"呢\", \"就\", \"是\", \"这\", \"一\", \"轮\", \"全\", \"球\", \"金\", \"融\", \"动\", \"荡\", \"的\", \"表\", \"现\"]}\n",
            "----\n",
            "./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/8k.wav\n",
            "{\"text\": \"深入地分析这一次全球金融动荡背后的根源\", \"timestamps\": [0.56, 0.72, 0.84, 1.00, 1.24, 1.76, 1.92, 2.12, 2.72, 2.92, 3.08, 3.20, 3.32, 3.48, 3.60, 3.72, 3.84, 4.00, 4.16], \"tokens\":[\"深\", \"入\", \"地\", \"分\", \"析\", \"这\", \"一\", \"次\", \"全\", \"球\", \"金\", \"融\", \"动\", \"荡\", \"背\", \"后\", \"的\", \"根\", \"源\"]}\n",
            "----\n",
            "num threads: 2\n",
            "decoding method: greedy_search\n",
            "Elapsed seconds: 1.830 s\n",
            "Real time factor (RTF): 1.830 / 15.289 = 0.120\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# int8 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx-offline \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-zh-wenet-wenetspeech/model.int8.onnx \\\n",
        "  --tokens=./sherpa-onnx-zh-wenet-wenetspeech/tokens.txt \\\n",
        "  ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "TKWqlFyHNM-c",
        "outputId": "963961d9-d382-490f-b06c-9afcff5d66a0"
      },
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx-offline --wenet-ctc-model=./sherpa-onnx-zh-wenet-wenetspeech/model.int8.onnx --tokens=./sherpa-onnx-zh-wenet-wenetspeech/tokens.txt ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/0.wav ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/1.wav ./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/8k.wav \n",
            "\n",
            "OfflineRecognizerConfig(feat_config=OfflineFeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename=\"\", decoder_filename=\"\", joiner_filename=\"\"), paraformer=OfflineParaformerModelConfig(model=\"\"), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=\"\"), whisper=OfflineWhisperModelConfig(encoder=\"\", decoder=\"\", language=\"\", task=\"transcribe\"), tdnn=OfflineTdnnModelConfig(model=\"\"), zipformer_ctc=OfflineZipformerCtcModelConfig(model=\"\"), wenet_ctc=OfflineWenetCtcModelConfig(model=\"./sherpa-onnx-zh-wenet-wenetspeech/model.int8.onnx\"), tokens=\"./sherpa-onnx-zh-wenet-wenetspeech/tokens.txt\", num_threads=2, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OfflineLMConfig(model=\"\", scale=0.5), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph=\"\", max_active=3000), decoding_method=\"greedy_search\", max_active_paths=4, hotwords_file=\"\", hotwords_score=1.5)\n",
            "Creating recognizer ...\n",
            "Started\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/offline-stream.cc:AcceptWaveformImpl:113 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "Done!\n",
            "\n",
            "./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/0.wav\n",
            "{\"text\": \"对我做了介绍那么我想说的是大家如果对我的研究感兴趣呢\", \"timestamps\": [0.48, 0.64, 0.76, 0.88, 1.04, 1.24, 1.96, 2.08, 2.28, 2.40, 2.52, 2.64, 2.76, 3.40, 3.52, 3.68, 3.76, 3.88, 3.96, 4.04, 4.16, 4.28, 4.40, 4.60, 4.76, 4.96], \"tokens\":[\"对\", \"我\", \"做\", \"了\", \"介\", \"绍\", \"那\", \"么\", \"我\", \"想\", \"说\", \"的\", \"是\", \"大\", \"家\", \"如\", \"果\", \"对\", \"我\", \"的\", \"研\", \"究\", \"感\", \"兴\", \"趣\", \"呢\"]}\n",
            "----\n",
            "./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/1.wav\n",
            "{\"text\": \"重点来想谈三个问题首先呢就是这一轮全球金融动荡的表现\", \"timestamps\": [0.32, 0.48, 0.60, 0.76, 0.92, 1.08, 1.20, 1.36, 1.48, 2.32, 2.48, 2.64, 2.76, 2.92, 3.20, 3.32, 3.44, 3.68, 3.84, 3.96, 4.08, 4.20, 4.32, 4.44, 4.60, 4.80], \"tokens\":[\"重\", \"点\", \"来\", \"想\", \"谈\", \"三\", \"个\", \"问\", \"题\", \"首\", \"先\", \"呢\", \"就\", \"是\", \"这\", \"一\", \"轮\", \"全\", \"球\", \"金\", \"融\", \"动\", \"荡\", \"的\", \"表\", \"现\"]}\n",
            "----\n",
            "./sherpa-onnx-zh-wenet-wenetspeech/test_wavs/8k.wav\n",
            "{\"text\": \"深入地分析这一次全球金融动荡背后的根源\", \"timestamps\": [0.56, 0.72, 0.84, 1.00, 1.24, 1.76, 1.92, 2.12, 2.72, 2.92, 3.08, 3.20, 3.32, 3.48, 3.60, 3.72, 3.84, 4.00, 4.16], \"tokens\":[\"深\", \"入\", \"地\", \"分\", \"析\", \"这\", \"一\", \"次\", \"全\", \"球\", \"金\", \"融\", \"动\", \"荡\", \"背\", \"后\", \"的\", \"根\", \"源\"]}\n",
            "----\n",
            "num threads: 2\n",
            "decoding method: greedy_search\n",
            "Elapsed seconds: 1.599 s\n",
            "Real time factor (RTF): 1.599 / 15.289 = 0.105\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 21
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# sherpa-onnx-zh-wenet-librispeech"
      ],
      "metadata": {
        "id": "Xrg6SdRTNV0k"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "git lfs install\n",
        "git clone https://huggingface.co/csukuangfj/sherpa-onnx-en-wenet-librispeech\n",
        "ls -lh sherpa-onnx-en-wenet-librispeech"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "72GxSy-2NjBY",
        "outputId": "59d06810-71d8-436a-efe0-c6ae89065b49"
      },
      "execution_count": 22,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Git LFS initialized.\n",
            "Cloning into 'sherpa-onnx-en-wenet-librispeech'...\n",
            "remote: Enumerating objects: 25, done.\u001b[K\n",
            "remote: Counting objects: 100% (22/22), done.\u001b[K\n",
            "remote: Compressing objects: 100% (21/21), done.\u001b[K\n",
            "remote: Total 25 (delta 1), reused 0 (delta 0), pack-reused 3\u001b[K\n",
            "Unpacking objects: 100% (25/25), 690.81 KiB | 7.12 MiB/s, done.\n",
            "Filtering content: 100% (4/4), 371.03 MiB | 66.20 MiB/s, done.\n",
            "total 372M\n",
            "-rw-r--r-- 1 root root  48M Nov 16 03:52 model.int8.onnx\n",
            "-rw-r--r-- 1 root root 138M Nov 16 03:52 model.onnx\n",
            "-rw-r--r-- 1 root root  48M Nov 16 03:52 model-streaming.int8.onnx\n",
            "-rw-r--r-- 1 root root 138M Nov 16 03:52 model-streaming.onnx\n",
            "-rw-r--r-- 1 root root  134 Nov 16 03:52 README.md\n",
            "drwxr-xr-x 2 root root 4.0K Nov 16 03:52 test_wavs\n",
            "-rwxr-xr-x 1 root root  69K Nov 16 03:52 tokens.txt\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Streaming decoding"
      ],
      "metadata": {
        "id": "JvITcEYrNYnP"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# float32 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-en-wenet-librispeech/model-streaming.onnx \\\n",
        "  --tokens=./sherpa-onnx-en-wenet-librispeech/tokens.txt \\\n",
        "  ./sherpa-onnx-en-wenet-librispeech/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-en-wenet-librispeech/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-en-wenet-librispeech/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UzGfzt7HNp7O",
        "outputId": "c2b0c71e-8d38-498e-d9bf-b72484337357"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx --wenet-ctc-model=./sherpa-onnx-en-wenet-librispeech/model-streaming.onnx --tokens=./sherpa-onnx-en-wenet-librispeech/tokens.txt ./sherpa-onnx-en-wenet-librispeech/test_wavs/0.wav ./sherpa-onnx-en-wenet-librispeech/test_wavs/1.wav ./sherpa-onnx-en-wenet-librispeech/test_wavs/8k.wav \n",
            "\n",
            "OnlineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OnlineModelConfig(transducer=OnlineTransducerModelConfig(encoder=\"\", decoder=\"\", joiner=\"\"), paraformer=OnlineParaformerModelConfig(encoder=\"\", decoder=\"\"), wenet_ctc=OnlineWenetCtcModelConfig(model=\"./sherpa-onnx-en-wenet-librispeech/model-streaming.onnx\", chunk_size=16, num_left_chunks=4), tokens=\"./sherpa-onnx-en-wenet-librispeech/tokens.txt\", num_threads=1, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OnlineLMConfig(model=\"\", scale=0.5), endpoint_config=EndpointConfig(rule1=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=2.4, min_utterance_length=0), rule2=EndpointRule(must_contain_nonsilence=True, min_trailing_silence=1.2, min_utterance_length=0), rule3=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=0, min_utterance_length=20)), enable_endpoint=True, max_active_paths=4, hotwords_score=1.5, hotwords_file=\"\", decoding_method=\"greedy_search\")\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/features.cc:AcceptWaveformImpl:85 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "./sherpa-onnx-en-wenet-librispeech/test_wavs/0.wav\n",
            "Elapsed seconds: 1.4, Real time factor (RTF): 0.2\n",
            " AFTER EARLYLY NIGHTFALL THE YELLOW LAMPS WOULD LIGHT UP HERE AND THERE THE SQUALID QUARTER OF THE BROFFELS\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \" AFTER EARLYLY NIGHTFALL THE YELLOW LAMPS WOULD LIGHT UP HERE AND THERE THE SQUALID QUARTER OF THE BROFFELS\", \"timestamps\": [0.16, 0.48, 0.60, 0.00, 0.24, 0.48, 0.16, 0.32, 0.04, 0.20, 0.36, 0.60, 0.20, 0.44, 0.00, 0.24, 0.00, 0.16, 0.28, 0.40, 0.12, 0.48, 0.00, 0.08, 0.20, 0.28, 0.40, 0.48], \"tokens\":[\" AFTER\", \" EAR\", \"LY\", \"LY\", \" NIGHT\", \"FALL\", \" THE\", \" YELLOW\", \" LAMP\", \"S\", \" WOULD\", \" LIGHT\", \" UP\", \" HERE\", \" AND\", \" THERE\", \" THE\", \" SQU\", \"AL\", \"ID\", \" QUARTER\", \" OF\", \" THE\", \" \", \"BRO\", \"FF\", \"EL\", \"S\"]}\n",
            "\n",
            "./sherpa-onnx-en-wenet-librispeech/test_wavs/1.wav\n",
            "Elapsed seconds: 2, Real time factor (RTF): 0.12\n",
            " GOD AS A DIRECT CONSEQUENCE OF THE SIN WHICH MAN THUS PUNISHED HAD GIVEN HER A LOVELY CHILD WHOSE PLACE WAS ON THAT SAME DISHONORED BOSOM TO CONNECT HER PARENTRO FOR EVER WITH THE RACE AND DESCENT OF MORTALS AND TO BE FINALLY A BLESSED SOUL IN HEAVEN\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \" GOD AS A DIRECT CONSEQUENCE OF THE SIN WHICH MAN THUS PUNISHED HAD GIVEN HER A LOVELY CHILD WHOSE PLACE WAS ON THAT SAME DISHONORED BOSOM TO CONNECT HER PARENTRO FOR EVER WITH THE RACE AND DESCENT OF MORTALS AND TO BE FINALLY A BLESSED SOUL IN HEAVEN\", \"timestamps\": [0.08, 0.40, 0.60, 0.16, 0.56, 0.48, 0.04, 0.20, 0.48, 0.08, 0.36, 0.44, 0.04, 0.24, 0.12, 0.32, 0.44, 0.00, 0.24, 0.40, 0.60, 0.20, 0.24, 0.32, 0.60, 0.28, 0.48, 0.08, 0.36, 0.12, 0.24, 0.40, 0.48, 0.08, 0.52, 0.20, 0.48, 0.04, 0.16, 0.12, 0.32, 0.56, 0.08, 0.28, 0.04, 0.40, 0.08, 0.32, 0.60, 0.52, 0.04, 0.20, 0.44, 0.00, 0.24, 0.44, 0.60, 0.36, 0.08, 0.28], \"tokens\":[\" GOD\", \" AS\", \" A\", \" DIRECT\", \" CONSEQUENCE\", \" OF\", \" THE\", \" SIN\", \" WHICH\", \" MAN\", \" THU\", \"S\", \" PUNISH\", \"ED\", \" HAD\", \" GIVE\", \"N\", \" HER\", \" A\", \" LOVE\", \"LY\", \" CHILD\", \" WHO\", \"SE\", \" PLACE\", \" WAS\", \" ON\", \" THAT\", \" SAME\", \" DISH\", \"ON\", \"OR\", \"ED\", \" BOSOM\", \" TO\", \" CONNECT\", \" HER\", \" PARENT\", \"RO\", \" FOR\", \" EVER\", \" WITH\", \" THE\", \" RACE\", \" AND\", \" DESCENT\", \" OF\", \" MORTAL\", \"S\", \" AND\", \" TO\", \" BE\", \" FINAL\", \"LY\", \" A\", \" BLESS\", \"ED\", \" SOUL\", \" IN\", \" HEAVEN\"]}\n",
            "\n",
            "./sherpa-onnx-en-wenet-librispeech/test_wavs/8k.wav\n",
            "Elapsed seconds: 1.1, Real time factor (RTF): 0.23\n",
            " YET THESE THOUGHTS AFFECTED HESTER PRYNNNE LESS WITH HOPE THAN APPREHENSION\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \" YET THESE THOUGHTS AFFECTED HESTER PRYNNNE LESS WITH HOPE THAN APPREHENSION\", \"timestamps\": [0.12, 0.40, 0.04, 0.16, 0.40, 0.12, 0.32, 0.48, 0.56, 0.60, 0.00, 0.04, 0.32, 0.04, 0.24, 0.08, 0.60], \"tokens\":[\" YET\", \" THESE\", \" THOUGHT\", \"S\", \" AFFECTED\", \" HE\", \"STER\", \" P\", \"RY\", \"N\", \"N\", \"NE\", \" LESS\", \" WITH\", \" HOPE\", \" THAN\", \" APPREHENSION\"]}\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# int8 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-en-wenet-librispeech/model-streaming.int8.onnx \\\n",
        "  --tokens=./sherpa-onnx-en-wenet-librispeech/tokens.txt \\\n",
        "  ./sherpa-onnx-en-wenet-librispeech/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-en-wenet-librispeech/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-en-wenet-librispeech/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "s7gyp-FrNxtu",
        "outputId": "3b9329ef-48ad-4443-eab9-18bd444487f6"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx --wenet-ctc-model=./sherpa-onnx-en-wenet-librispeech/model-streaming.int8.onnx --tokens=./sherpa-onnx-en-wenet-librispeech/tokens.txt ./sherpa-onnx-en-wenet-librispeech/test_wavs/0.wav ./sherpa-onnx-en-wenet-librispeech/test_wavs/1.wav ./sherpa-onnx-en-wenet-librispeech/test_wavs/8k.wav \n",
            "\n",
            "OnlineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OnlineModelConfig(transducer=OnlineTransducerModelConfig(encoder=\"\", decoder=\"\", joiner=\"\"), paraformer=OnlineParaformerModelConfig(encoder=\"\", decoder=\"\"), wenet_ctc=OnlineWenetCtcModelConfig(model=\"./sherpa-onnx-en-wenet-librispeech/model-streaming.int8.onnx\", chunk_size=16, num_left_chunks=4), tokens=\"./sherpa-onnx-en-wenet-librispeech/tokens.txt\", num_threads=1, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OnlineLMConfig(model=\"\", scale=0.5), endpoint_config=EndpointConfig(rule1=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=2.4, min_utterance_length=0), rule2=EndpointRule(must_contain_nonsilence=True, min_trailing_silence=1.2, min_utterance_length=0), rule3=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=0, min_utterance_length=20)), enable_endpoint=True, max_active_paths=4, hotwords_score=1.5, hotwords_file=\"\", decoding_method=\"greedy_search\")\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/features.cc:AcceptWaveformImpl:85 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "./sherpa-onnx-en-wenet-librispeech/test_wavs/0.wav\n",
            "Elapsed seconds: 1.1, Real time factor (RTF): 0.16\n",
            " AFTER EARLYLY NIGHTFALL THE YELLOW LAMPS WOULD LIGHT UP HERE AND THERE THE SQUALID QUARTER OF THE BROFFTHELS\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \" AFTER EARLYLY NIGHTFALL THE YELLOW LAMPS WOULD LIGHT UP HERE AND THERE THE SQUALID QUARTER OF THE BROFFTHELS\", \"timestamps\": [0.16, 0.48, 0.60, 0.00, 0.24, 0.48, 0.16, 0.32, 0.04, 0.20, 0.36, 0.60, 0.20, 0.44, 0.00, 0.20, 0.00, 0.16, 0.28, 0.40, 0.12, 0.48, 0.00, 0.08, 0.20, 0.28, 0.32, 0.40, 0.48], \"tokens\":[\" AFTER\", \" EAR\", \"LY\", \"LY\", \" NIGHT\", \"FALL\", \" THE\", \" YELLOW\", \" LAMP\", \"S\", \" WOULD\", \" LIGHT\", \" UP\", \" HERE\", \" AND\", \" THERE\", \" THE\", \" SQU\", \"AL\", \"ID\", \" QUARTER\", \" OF\", \" THE\", \" \", \"BRO\", \"FF\", \"TH\", \"EL\", \"S\"]}\n",
            "\n",
            "./sherpa-onnx-en-wenet-librispeech/test_wavs/1.wav\n",
            "Elapsed seconds: 1.6, Real time factor (RTF): 0.096\n",
            " GOD AS A DIRECT CONSEQUENCE OF THE SIN WHICH MAN THUS PUNISHED HAD GIVEN HER A LOVELY CHILD WHOSE PLACE WAS ON THAT SAME DISHONORED BOSOM TO CONNECT HER PARENTRO FOR EVER WITH THE RACE AND DESCENT OF MORTALS AND TO BE FINALLY A BLESSED SOUL IN HEAVEN\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \" GOD AS A DIRECT CONSEQUENCE OF THE SIN WHICH MAN THUS PUNISHED HAD GIVEN HER A LOVELY CHILD WHOSE PLACE WAS ON THAT SAME DISHONORED BOSOM TO CONNECT HER PARENTRO FOR EVER WITH THE RACE AND DESCENT OF MORTALS AND TO BE FINALLY A BLESSED SOUL IN HEAVEN\", \"timestamps\": [0.08, 0.40, 0.60, 0.16, 0.60, 0.48, 0.04, 0.20, 0.48, 0.08, 0.36, 0.44, 0.04, 0.24, 0.12, 0.32, 0.44, 0.00, 0.24, 0.40, 0.60, 0.20, 0.24, 0.32, 0.60, 0.28, 0.48, 0.08, 0.36, 0.12, 0.24, 0.40, 0.48, 0.08, 0.52, 0.20, 0.48, 0.04, 0.16, 0.12, 0.32, 0.56, 0.08, 0.28, 0.04, 0.40, 0.08, 0.32, 0.60, 0.52, 0.04, 0.20, 0.44, 0.00, 0.24, 0.44, 0.60, 0.36, 0.08, 0.28], \"tokens\":[\" GOD\", \" AS\", \" A\", \" DIRECT\", \" CONSEQUENCE\", \" OF\", \" THE\", \" SIN\", \" WHICH\", \" MAN\", \" THU\", \"S\", \" PUNISH\", \"ED\", \" HAD\", \" GIVE\", \"N\", \" HER\", \" A\", \" LOVE\", \"LY\", \" CHILD\", \" WHO\", \"SE\", \" PLACE\", \" WAS\", \" ON\", \" THAT\", \" SAME\", \" DISH\", \"ON\", \"OR\", \"ED\", \" BOSOM\", \" TO\", \" CONNECT\", \" HER\", \" PARENT\", \"RO\", \" FOR\", \" EVER\", \" WITH\", \" THE\", \" RACE\", \" AND\", \" DESCENT\", \" OF\", \" MORTAL\", \"S\", \" AND\", \" TO\", \" BE\", \" FINAL\", \"LY\", \" A\", \" BLESS\", \"ED\", \" SOUL\", \" IN\", \" HEAVEN\"]}\n",
            "\n",
            "./sherpa-onnx-en-wenet-librispeech/test_wavs/8k.wav\n",
            "Elapsed seconds: 0.86, Real time factor (RTF): 0.18\n",
            " YET THESE THOUGHTS AFFECTED HESTER PRYNNNE LESS WITH HOPE THAN APPREHENSION\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \" YET THESE THOUGHTS AFFECTED HESTER PRYNNNE LESS WITH HOPE THAN APPREHENSION\", \"timestamps\": [0.08, 0.40, 0.04, 0.16, 0.40, 0.12, 0.32, 0.48, 0.56, 0.60, 0.00, 0.04, 0.32, 0.04, 0.24, 0.08, 0.60], \"tokens\":[\" YET\", \" THESE\", \" THOUGHT\", \"S\", \" AFFECTED\", \" HE\", \"STER\", \" P\", \"RY\", \"N\", \"N\", \"NE\", \" LESS\", \" WITH\", \" HOPE\", \" THAN\", \" APPREHENSION\"]}\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Non-streaming-decoding"
      ],
      "metadata": {
        "id": "D5-bzWqZNaG-"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# float32 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx-offline \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-en-wenet-librispeech/model.onnx \\\n",
        "  --tokens=./sherpa-onnx-en-wenet-librispeech/tokens.txt \\\n",
        "  ./sherpa-onnx-en-wenet-librispeech/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-en-wenet-librispeech/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-en-wenet-librispeech/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uasvLI2KNwm3",
        "outputId": "a581cbcb-b9c5-4331-d599-36c1dd048d2f"
      },
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx-offline --wenet-ctc-model=./sherpa-onnx-en-wenet-librispeech/model.onnx --tokens=./sherpa-onnx-en-wenet-librispeech/tokens.txt ./sherpa-onnx-en-wenet-librispeech/test_wavs/0.wav ./sherpa-onnx-en-wenet-librispeech/test_wavs/1.wav ./sherpa-onnx-en-wenet-librispeech/test_wavs/8k.wav \n",
            "\n",
            "OfflineRecognizerConfig(feat_config=OfflineFeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename=\"\", decoder_filename=\"\", joiner_filename=\"\"), paraformer=OfflineParaformerModelConfig(model=\"\"), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=\"\"), whisper=OfflineWhisperModelConfig(encoder=\"\", decoder=\"\", language=\"\", task=\"transcribe\"), tdnn=OfflineTdnnModelConfig(model=\"\"), zipformer_ctc=OfflineZipformerCtcModelConfig(model=\"\"), wenet_ctc=OfflineWenetCtcModelConfig(model=\"./sherpa-onnx-en-wenet-librispeech/model.onnx\"), tokens=\"./sherpa-onnx-en-wenet-librispeech/tokens.txt\", num_threads=2, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OfflineLMConfig(model=\"\", scale=0.5), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph=\"\", max_active=3000), decoding_method=\"greedy_search\", max_active_paths=4, hotwords_file=\"\", hotwords_score=1.5)\n",
            "Creating recognizer ...\n",
            "Started\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/offline-stream.cc:AcceptWaveformImpl:113 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "Done!\n",
            "\n",
            "./sherpa-onnx-en-wenet-librispeech/test_wavs/0.wav\n",
            "{\"text\": \" AFTER EARLY NIGHTFALL THE YELLOW LAMPS WOULD LIGHT UP HERE AND THERE THE SQUALID QUARTER OF THE BROTHELS\", \"timestamps\": [0.80, 1.12, 1.24, 1.52, 1.76, 2.08, 2.24, 2.60, 2.76, 2.92, 3.16, 3.40, 3.68, 3.84, 4.08, 4.48, 4.64, 4.76, 4.88, 5.24, 5.60, 5.76, 5.84, 5.92, 6.00, 6.16, 6.24], \"tokens\":[\" AFTER\", \" EAR\", \"LY\", \" NIGHT\", \"FALL\", \" THE\", \" YELLOW\", \" LAMP\", \"S\", \" WOULD\", \" LIGHT\", \" UP\", \" HERE\", \" AND\", \" THERE\", \" THE\", \" SQU\", \"AL\", \"ID\", \" QUARTER\", \" OF\", \" THE\", \" \", \"BRO\", \"TH\", \"EL\", \"S\"]}\n",
            "----\n",
            "./sherpa-onnx-en-wenet-librispeech/test_wavs/1.wav\n",
            "{\"text\": \" GOD AS A DIRECT CONSEQUENCE OF THE SIN WHICH MAN THUS PUNISHED HAD GIVEN HER A LOVELY CHILD WHOSE PLACE WAS ON THAT SAME DISHONOURED BOSOM TO CONNECT HER PARENT FOR EVER WITH THE RACE AND DESCENT OF MORTALS AND TO BE FINALLY A BLESSED SOUL IN HEAVEN\", \"timestamps\": [0.72, 1.04, 1.20, 1.44, 1.84, 2.40, 2.56, 2.76, 3.04, 3.28, 3.56, 3.64, 3.88, 4.08, 4.60, 4.80, 4.92, 5.12, 5.36, 5.52, 5.72, 6.00, 6.64, 6.72, 7.00, 7.32, 7.52, 7.76, 8.04, 8.40, 8.56, 8.72, 8.80, 9.00, 9.48, 9.80, 10.08, 10.28, 11.00, 11.20, 11.44, 11.60, 11.80, 12.20, 12.56, 12.88, 13.12, 13.36, 13.96, 14.12, 14.28, 14.48, 14.72, 14.96, 15.16, 15.28, 15.72, 16.04, 16.24], \"tokens\":[\" GOD\", \" AS\", \" A\", \" DIRECT\", \" CONSEQUENCE\", \" OF\", \" THE\", \" SIN\", \" WHICH\", \" MAN\", \" THU\", \"S\", \" PUNISH\", \"ED\", \" HAD\", \" GIVE\", \"N\", \" HER\", \" A\", \" LOVE\", \"LY\", \" CHILD\", \" WHO\", \"SE\", \" PLACE\", \" WAS\", \" ON\", \" THAT\", \" SAME\", \" DISH\", \"ON\", \"OUR\", \"ED\", \" BOSOM\", \" TO\", \" CONNECT\", \" HER\", \" PARENT\", \" FOR\", \" EVER\", \" WITH\", \" THE\", \" RACE\", \" AND\", \" DESCENT\", \" OF\", \" MORTAL\", \"S\", \" AND\", \" TO\", \" BE\", \" FINAL\", \"LY\", \" A\", \" BLESS\", \"ED\", \" SOUL\", \" IN\", \" HEAVEN\"]}\n",
            "----\n",
            "./sherpa-onnx-en-wenet-librispeech/test_wavs/8k.wav\n",
            "{\"text\": \" YET THESE THOUGHTS AFFECTED HESTER PRYNNE LESS WITH HOPE THAN APPREHENSION\", \"timestamps\": [0.76, 1.00, 1.32, 1.44, 1.68, 2.04, 2.24, 2.40, 2.48, 2.56, 2.60, 2.88, 3.24, 3.44, 3.92, 4.44], \"tokens\":[\" YET\", \" THESE\", \" THOUGHT\", \"S\", \" AFFECTED\", \" HE\", \"STER\", \" P\", \"RY\", \"N\", \"NE\", \" LESS\", \" WITH\", \" HOPE\", \" THAN\", \" APPREHENSION\"]}\n",
            "----\n",
            "num threads: 2\n",
            "decoding method: greedy_search\n",
            "Elapsed seconds: 3.379 s\n",
            "Real time factor (RTF): 3.379 / 28.165 = 0.120\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# int8 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx-offline \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-en-wenet-librispeech/model.int8.onnx \\\n",
        "  --tokens=./sherpa-onnx-en-wenet-librispeech/tokens.txt \\\n",
        "  ./sherpa-onnx-en-wenet-librispeech/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-en-wenet-librispeech/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-en-wenet-librispeech/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UXwGaawhN4i7",
        "outputId": "3efdb1af-7e7f-4b92-dcd2-05a55826e23a"
      },
      "execution_count": 26,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx-offline --wenet-ctc-model=./sherpa-onnx-en-wenet-librispeech/model.int8.onnx --tokens=./sherpa-onnx-en-wenet-librispeech/tokens.txt ./sherpa-onnx-en-wenet-librispeech/test_wavs/0.wav ./sherpa-onnx-en-wenet-librispeech/test_wavs/1.wav ./sherpa-onnx-en-wenet-librispeech/test_wavs/8k.wav \n",
            "\n",
            "OfflineRecognizerConfig(feat_config=OfflineFeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename=\"\", decoder_filename=\"\", joiner_filename=\"\"), paraformer=OfflineParaformerModelConfig(model=\"\"), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=\"\"), whisper=OfflineWhisperModelConfig(encoder=\"\", decoder=\"\", language=\"\", task=\"transcribe\"), tdnn=OfflineTdnnModelConfig(model=\"\"), zipformer_ctc=OfflineZipformerCtcModelConfig(model=\"\"), wenet_ctc=OfflineWenetCtcModelConfig(model=\"./sherpa-onnx-en-wenet-librispeech/model.int8.onnx\"), tokens=\"./sherpa-onnx-en-wenet-librispeech/tokens.txt\", num_threads=2, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OfflineLMConfig(model=\"\", scale=0.5), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph=\"\", max_active=3000), decoding_method=\"greedy_search\", max_active_paths=4, hotwords_file=\"\", hotwords_score=1.5)\n",
            "Creating recognizer ...\n",
            "Started\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/offline-stream.cc:AcceptWaveformImpl:113 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "Done!\n",
            "\n",
            "./sherpa-onnx-en-wenet-librispeech/test_wavs/0.wav\n",
            "{\"text\": \" AFTER EARLY NIGHTFALL THE YELLOW LAMPS WOULD LIGHT UP HERE AND THERE THE SQUALID QUARTER OF THE BROTHELS\", \"timestamps\": [0.80, 1.12, 1.24, 1.52, 1.76, 2.08, 2.24, 2.60, 2.76, 2.92, 3.16, 3.40, 3.68, 3.84, 4.08, 4.48, 4.64, 4.76, 4.88, 5.24, 5.60, 5.76, 5.84, 5.92, 6.00, 6.16, 6.24], \"tokens\":[\" AFTER\", \" EAR\", \"LY\", \" NIGHT\", \"FALL\", \" THE\", \" YELLOW\", \" LAMP\", \"S\", \" WOULD\", \" LIGHT\", \" UP\", \" HERE\", \" AND\", \" THERE\", \" THE\", \" SQU\", \"AL\", \"ID\", \" QUARTER\", \" OF\", \" THE\", \" \", \"BRO\", \"TH\", \"EL\", \"S\"]}\n",
            "----\n",
            "./sherpa-onnx-en-wenet-librispeech/test_wavs/1.wav\n",
            "{\"text\": \" GOD AS A DIRECT CONSEQUENCE OF THE SIN WHICH MAN THUS PUNISHED HAD GIVEN HER A LOVELY CHILD WHOSE PLACE WAS ON THAT SAME DISHONOURED BOSOM TO CONNECT HER PARENT FOR EVER WITH THE RACE AND DESCENT OF MORTALS AND TO BE FINALLY A BLESSED SOUL IN HEAVEN\", \"timestamps\": [0.72, 1.04, 1.20, 1.44, 1.84, 2.40, 2.60, 2.76, 3.04, 3.28, 3.56, 3.64, 3.88, 4.08, 4.60, 4.80, 4.92, 5.12, 5.36, 5.52, 5.72, 6.00, 6.64, 6.72, 7.00, 7.32, 7.52, 7.76, 8.04, 8.40, 8.56, 8.72, 8.80, 9.04, 9.48, 9.80, 10.08, 10.28, 11.00, 11.20, 11.44, 11.60, 11.80, 12.20, 12.56, 12.88, 13.12, 13.36, 13.96, 14.12, 14.28, 14.48, 14.72, 14.96, 15.16, 15.28, 15.72, 16.04, 16.24], \"tokens\":[\" GOD\", \" AS\", \" A\", \" DIRECT\", \" CONSEQUENCE\", \" OF\", \" THE\", \" SIN\", \" WHICH\", \" MAN\", \" THU\", \"S\", \" PUNISH\", \"ED\", \" HAD\", \" GIVE\", \"N\", \" HER\", \" A\", \" LOVE\", \"LY\", \" CHILD\", \" WHO\", \"SE\", \" PLACE\", \" WAS\", \" ON\", \" THAT\", \" SAME\", \" DISH\", \"ON\", \"OUR\", \"ED\", \" BOSOM\", \" TO\", \" CONNECT\", \" HER\", \" PARENT\", \" FOR\", \" EVER\", \" WITH\", \" THE\", \" RACE\", \" AND\", \" DESCENT\", \" OF\", \" MORTAL\", \"S\", \" AND\", \" TO\", \" BE\", \" FINAL\", \"LY\", \" A\", \" BLESS\", \"ED\", \" SOUL\", \" IN\", \" HEAVEN\"]}\n",
            "----\n",
            "./sherpa-onnx-en-wenet-librispeech/test_wavs/8k.wav\n",
            "{\"text\": \" YET THESE THOUGHTS AFFECTED HESTER PRYNNE LESS WITH HOPE THAN APPREHENSION\", \"timestamps\": [0.76, 1.00, 1.32, 1.44, 1.68, 2.04, 2.24, 2.40, 2.48, 2.56, 2.60, 2.88, 3.24, 3.44, 3.92, 4.44], \"tokens\":[\" YET\", \" THESE\", \" THOUGHT\", \"S\", \" AFFECTED\", \" HE\", \"STER\", \" P\", \"RY\", \"N\", \"NE\", \" LESS\", \" WITH\", \" HOPE\", \" THAN\", \" APPREHENSION\"]}\n",
            "----\n",
            "num threads: 2\n",
            "decoding method: greedy_search\n",
            "Elapsed seconds: 1.240 s\n",
            "Real time factor (RTF): 1.240 / 28.165 = 0.044\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 26
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# sherpa-onnx-zh-wenet-gigaspeech"
      ],
      "metadata": {
        "id": "I1aZ9ClcNXCf"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "git lfs install\n",
        "git clone https://huggingface.co/csukuangfj/sherpa-onnx-en-wenet-gigaspeech\n",
        "ls -lh sherpa-onnx-en-wenet-gigaspeech"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "bP_HXTNbN9AH",
        "outputId": "b792fe5e-3497-45f7-cd73-be501d913f91"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Git LFS initialized.\n",
            "Cloning into 'sherpa-onnx-en-wenet-gigaspeech'...\n",
            "remote: Enumerating objects: 25, done.\u001b[K\n",
            "remote: Counting objects: 100% (22/22), done.\u001b[K\n",
            "remote: Compressing objects: 100% (21/21), done.\u001b[K\n",
            "remote: Total 25 (delta 1), reused 0 (delta 0), pack-reused 3\u001b[K\n",
            "Unpacking objects: 100% (25/25), 690.77 KiB | 7.20 MiB/s, done.\n",
            "Filtering content: 100% (4/4), 975.77 MiB | 43.30 MiB/s, done.\n",
            "total 976M\n",
            "-rw-r--r-- 1 root root 142M Nov 16 03:53 model.int8.onnx\n",
            "-rw-r--r-- 1 root root 347M Nov 16 03:53 model.onnx\n",
            "-rw-r--r-- 1 root root 142M Nov 16 03:53 model-streaming.int8.onnx\n",
            "-rw-r--r-- 1 root root 347M Nov 16 03:53 model-streaming.onnx\n",
            "-rw-r--r-- 1 root root  133 Nov 16 03:53 README.md\n",
            "drwxr-xr-x 2 root root 4.0K Nov 16 03:53 test_wavs\n",
            "-rwxr-xr-x 1 root root  70K Nov 16 03:53 tokens.txt\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Streaming decoding"
      ],
      "metadata": {
        "id": "FmfgaNY2Ne4P"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# float32 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-en-wenet-gigaspeech/model-streaming.onnx \\\n",
        "  --tokens=./sherpa-onnx-en-wenet-gigaspeech/tokens.txt \\\n",
        "  ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "UTlN5MIFN8vX",
        "outputId": "c10a34fa-aca1-4ae9-bd3a-f41c48a95c2c"
      },
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx --wenet-ctc-model=./sherpa-onnx-en-wenet-gigaspeech/model-streaming.onnx --tokens=./sherpa-onnx-en-wenet-gigaspeech/tokens.txt ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/0.wav ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/1.wav ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/8k.wav \n",
            "\n",
            "OnlineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OnlineModelConfig(transducer=OnlineTransducerModelConfig(encoder=\"\", decoder=\"\", joiner=\"\"), paraformer=OnlineParaformerModelConfig(encoder=\"\", decoder=\"\"), wenet_ctc=OnlineWenetCtcModelConfig(model=\"./sherpa-onnx-en-wenet-gigaspeech/model-streaming.onnx\", chunk_size=16, num_left_chunks=4), tokens=\"./sherpa-onnx-en-wenet-gigaspeech/tokens.txt\", num_threads=1, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OnlineLMConfig(model=\"\", scale=0.5), endpoint_config=EndpointConfig(rule1=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=2.4, min_utterance_length=0), rule2=EndpointRule(must_contain_nonsilence=True, min_trailing_silence=1.2, min_utterance_length=0), rule3=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=0, min_utterance_length=20)), enable_endpoint=True, max_active_paths=4, hotwords_score=1.5, hotwords_file=\"\", decoding_method=\"greedy_search\")\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/features.cc:AcceptWaveformImpl:85 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "./sherpa-onnx-en-wenet-gigaspeech/test_wavs/0.wav\n",
            "Elapsed seconds: 3.9, Real time factor (RTF): 0.6\n",
            " AFTER EARLY EARLY NIGHTFALL FALLLL THE YELLOWLO LAMPS WOULD LIGHT LIGHT UP HERE AND HERE AND THERE THERE THE SQUALILID-LOLID QUARTER OF THE OF THE BROTHELSELS\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \" AFTER EARLY EARLY NIGHTFALL FALLLL THE YELLOWLO LAMPS WOULD LIGHT LIGHT UP HERE AND HERE AND THERE THERE THE SQUALILID-LOLID QUARTER OF THE OF THE BROTHELSELS\", \"timestamps\": [0.40, 0.04, 0.24, 0.48, 0.04, 0.12, 0.28, 0.32, 0.44, 0.56, 0.16, 0.36, 0.48, 0.60, 0.08, 0.32, 0.48, 0.00, 0.12, 0.24, 0.36, 0.48, 0.12, 0.32, 0.44, 0.52, 0.60, 0.00, 0.04, 0.08, 0.20, 0.24, 0.32, 0.40, 0.04, 0.12, 0.24, 0.32, 0.44, 0.56, 0.00, 0.08, 0.20, 0.28], \"tokens\":[\" AFTER\", \" EARLY\", \" EARLY\", \" NIGHT\", \"FA\", \"LL\", \" FALL\", \"LL\", \" THE\", \" YELLOW\", \"LO\", \" LAMP\", \"S\", \" WOULD\", \" LIGHT\", \" LIGHT\", \" UP\", \" HERE\", \" AND\", \" HERE\", \" AND\", \" THERE\", \" THERE\", \" THE\", \" S\", \"QUA\", \"LI\", \"LI\", \"D\", \"-\", \"LO\", \"LI\", \"D\", \" QUARTER\", \" OF\", \" THE\", \" OF\", \" THE\", \" BRO\", \"T\", \"HEL\", \"S\", \"EL\", \"S\"]}\n",
            "\n",
            "./sherpa-onnx-en-wenet-gigaspeech/test_wavs/1.wav\n",
            "Elapsed seconds: 6.1, Real time factor (RTF): 0.36\n",
            " GOD AS IT IS A DIRECT CONSEQUENCE CONSEQUENCE OF THIS OF THE SIN WHICH WHICH MAN THUS PUT PUNISHED HAD GIVEN HER GIVEN HER A LOVELY LOVELY CHILD WHOSE PLACE PLACE WAS ON ON THAT SAME DAME DISHONORED HONORARDED BOSOM TO TO CONNECT HER PAIR PARENT FOR EVER WITH HER WITH THE RACE ACE AND DESCENTMENT OF MORTAL MORTALS AND AND TO BE FINALLY FINALLY A BLESS LESS SOUL ILL IN HEAVEN\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \" GOD AS IT IS A DIRECT CONSEQUENCE CONSEQUENCE OF THIS OF THE SIN WHICH WHICH MAN THUS PUT PUNISHED HAD GIVEN HER GIVEN HER A LOVELY LOVELY CHILD WHOSE PLACE PLACE WAS ON ON THAT SAME DAME DISHONORED HONORARDED BOSOM TO TO CONNECT HER PAIR PARENT FOR EVER WITH HER WITH THE RACE ACE AND DESCENTMENT OF MORTAL MORTALS AND AND TO BE FINALLY FINALLY A BLESS LESS SOUL ILL IN HEAVEN\", \"timestamps\": [0.36, 0.00, 0.08, 0.20, 0.32, 0.44, 0.04, 0.24, 0.04, 0.12, 0.24, 0.36, 0.48, 0.00, 0.20, 0.40, 0.60, 0.16, 0.36, 0.56, 0.40, 0.56, 0.12, 0.24, 0.36, 0.48, 0.00, 0.20, 0.52, 0.48, 0.08, 0.28, 0.52, 0.00, 0.24, 0.40, 0.56, 0.16, 0.24, 0.36, 0.52, 0.00, 0.04, 0.16, 0.24, 0.28, 0.32, 0.36, 0.48, 0.56, 0.04, 0.28, 0.48, 0.00, 0.16, 0.40, 0.40, 0.52, 0.08, 0.20, 0.28, 0.40, 0.52, 0.16, 0.24, 0.36, 0.48, 0.52, 0.00, 0.20, 0.40, 0.52, 0.16, 0.36, 0.04, 0.24, 0.36, 0.44, 0.00, 0.20, 0.48, 0.60, 0.20, 0.56, 0.20, 0.28, 0.36, 0.48], \"tokens\":[\" GOD\", \" AS\", \" IT\", \" IS\", \" A\", \" DIRECT\", \" CONSEQUENCE\", \" CONSEQUENCE\", \" OF\", \" THIS\", \" OF\", \" THE\", \" SIN\", \" WHICH\", \" WHICH\", \" MAN\", \" THUS\", \" PUT\", \" PUNISH\", \"ED\", \" HAD\", \" GIVEN\", \" HER\", \" GIVEN\", \" HER\", \" A\", \" LOVELY\", \" LOVELY\", \" CHILD\", \" WHOSE\", \" PLACE\", \" PLACE\", \" WAS\", \" ON\", \" ON\", \" THAT\", \" SAME\", \" DAM\", \"E\", \" DISH\", \"ON\", \"OR\", \"ED\", \" HONOR\", \"ARD\", \"ED\", \" BO\", \"S\", \"O\", \"M\", \" TO\", \" TO\", \" CONNECT\", \" HER\", \" PAIR\", \" PARENT\", \" FOR\", \" EVER\", \" WITH\", \" HER\", \" WITH\", \" THE\", \" RACE\", \" A\", \"CE\", \" AND\", \" DE\", \"S\", \"CENT\", \"MENT\", \" OF\", \" MORTAL\", \" MORTAL\", \"S\", \" AND\", \" AND\", \" TO\", \" BE\", \" FINALLY\", \" FINALLY\", \" A\", \" BLESS\", \" LESS\", \" SOUL\", \" I\", \"LL\", \" IN\", \" HEAVEN\"]}\n",
            "\n",
            "./sherpa-onnx-en-wenet-gigaspeech/test_wavs/8k.wav\n",
            "Elapsed seconds: 3.2, Real time factor (RTF): 0.66\n",
            " YET THESE THOUGHTS THOUGHTS AFFECTED AFFECTED HESTER PRIN PRIN LESS WITH WITH HOPE THAN APPREHENREHENSION\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \" YET THESE THOUGHTS THOUGHTS AFFECTED AFFECTED HESTER PRIN PRIN LESS WITH WITH HOPE THAN APPREHENREHENSION\", \"timestamps\": [0.40, 0.00, 0.16, 0.36, 0.04, 0.24, 0.40, 0.56, 0.08, 0.12, 0.32, 0.36, 0.00, 0.16, 0.36, 0.52, 0.36, 0.52, 0.00, 0.08, 0.20, 0.28, 0.40, 0.48], \"tokens\":[\" YET\", \" THESE\", \" THOUGHTS\", \" THOUGHTS\", \" AFFECTED\", \" AFFECTED\", \" HE\", \"STER\", \" PRI\", \"N\", \" PRI\", \"N\", \" LESS\", \" WITH\", \" WITH\", \" HOPE\", \" THAN\", \" APP\", \"RE\", \"HEN\", \"RE\", \"HEN\", \"S\", \"ION\"]}\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# int8 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-en-wenet-gigaspeech/model-streaming.int8.onnx \\\n",
        "  --tokens=./sherpa-onnx-en-wenet-gigaspeech/tokens.txt \\\n",
        "  ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EXjffuAoOLZ7",
        "outputId": "8fbc3936-17e0-4c3a-9d65-4a3180bdd885"
      },
      "execution_count": 29,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx --wenet-ctc-model=./sherpa-onnx-en-wenet-gigaspeech/model-streaming.int8.onnx --tokens=./sherpa-onnx-en-wenet-gigaspeech/tokens.txt ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/0.wav ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/1.wav ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/8k.wav \n",
            "\n",
            "OnlineRecognizerConfig(feat_config=FeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OnlineModelConfig(transducer=OnlineTransducerModelConfig(encoder=\"\", decoder=\"\", joiner=\"\"), paraformer=OnlineParaformerModelConfig(encoder=\"\", decoder=\"\"), wenet_ctc=OnlineWenetCtcModelConfig(model=\"./sherpa-onnx-en-wenet-gigaspeech/model-streaming.int8.onnx\", chunk_size=16, num_left_chunks=4), tokens=\"./sherpa-onnx-en-wenet-gigaspeech/tokens.txt\", num_threads=1, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OnlineLMConfig(model=\"\", scale=0.5), endpoint_config=EndpointConfig(rule1=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=2.4, min_utterance_length=0), rule2=EndpointRule(must_contain_nonsilence=True, min_trailing_silence=1.2, min_utterance_length=0), rule3=EndpointRule(must_contain_nonsilence=False, min_trailing_silence=0, min_utterance_length=20)), enable_endpoint=True, max_active_paths=4, hotwords_score=1.5, hotwords_file=\"\", decoding_method=\"greedy_search\")\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/features.cc:AcceptWaveformImpl:85 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "./sherpa-onnx-en-wenet-gigaspeech/test_wavs/0.wav\n",
            "Elapsed seconds: 3.2, Real time factor (RTF): 0.48\n",
            " AFTER EARLY EARLY NIGHTFALL FALLLL THE YELLOWLO LAMPS WOULD LIGHT LIGHT UP HERE AND HERE AND THERE THERE THE SQUALILID-LID QUARTER OF THERE OF THE BROTHELSELS\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \" AFTER EARLY EARLY NIGHTFALL FALLLL THE YELLOWLO LAMPS WOULD LIGHT LIGHT UP HERE AND HERE AND THERE THERE THE SQUALILID-LID QUARTER OF THERE OF THE BROTHELSELS\", \"timestamps\": [0.40, 0.04, 0.24, 0.48, 0.04, 0.12, 0.28, 0.32, 0.44, 0.56, 0.16, 0.36, 0.48, 0.60, 0.08, 0.32, 0.48, 0.00, 0.12, 0.24, 0.36, 0.48, 0.12, 0.32, 0.44, 0.52, 0.60, 0.00, 0.04, 0.08, 0.20, 0.28, 0.40, 0.04, 0.12, 0.24, 0.32, 0.44, 0.56, 0.00, 0.08, 0.20, 0.28], \"tokens\":[\" AFTER\", \" EARLY\", \" EARLY\", \" NIGHT\", \"FA\", \"LL\", \" FALL\", \"LL\", \" THE\", \" YELLOW\", \"LO\", \" LAMP\", \"S\", \" WOULD\", \" LIGHT\", \" LIGHT\", \" UP\", \" HERE\", \" AND\", \" HERE\", \" AND\", \" THERE\", \" THERE\", \" THE\", \" S\", \"QUA\", \"LI\", \"LI\", \"D\", \"-\", \"LI\", \"D\", \" QUARTER\", \" OF\", \" THERE\", \" OF\", \" THE\", \" BRO\", \"T\", \"HEL\", \"S\", \"EL\", \"S\"]}\n",
            "\n",
            "./sherpa-onnx-en-wenet-gigaspeech/test_wavs/1.wav\n",
            "Elapsed seconds: 4.8, Real time factor (RTF): 0.29\n",
            " GOD AS IT IS A DIRECT CONSEQUENCE CONSEQUENCE OF THIS OF THE SIN WHICH WHICH MAN THUS PUT PUNISHED HAD GIVEN HER GIVEN HER A LOVELY LOVELY CHILD WHOSE PLACE PLACE WAS ON ON THAT SAME DAME DISHONOREDARDED BOSOM TO TO CONNECT HER PAIR PARENT FOR EVER WITH HER WITH THE RACE ACE AND DESCENTMENT OF MORTAL MORTALS AND AND TO BE FINALLY FINALLY A BLESS LESS SOUL ILL IN HEAVEN\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \" GOD AS IT IS A DIRECT CONSEQUENCE CONSEQUENCE OF THIS OF THE SIN WHICH WHICH MAN THUS PUT PUNISHED HAD GIVEN HER GIVEN HER A LOVELY LOVELY CHILD WHOSE PLACE PLACE WAS ON ON THAT SAME DAME DISHONOREDARDED BOSOM TO TO CONNECT HER PAIR PARENT FOR EVER WITH HER WITH THE RACE ACE AND DESCENTMENT OF MORTAL MORTALS AND AND TO BE FINALLY FINALLY A BLESS LESS SOUL ILL IN HEAVEN\", \"timestamps\": [0.36, 0.00, 0.08, 0.20, 0.32, 0.44, 0.04, 0.24, 0.04, 0.12, 0.24, 0.36, 0.48, 0.00, 0.20, 0.40, 0.60, 0.16, 0.36, 0.56, 0.40, 0.56, 0.12, 0.24, 0.36, 0.48, 0.00, 0.20, 0.52, 0.48, 0.08, 0.28, 0.52, 0.00, 0.24, 0.40, 0.56, 0.16, 0.24, 0.36, 0.52, 0.00, 0.04, 0.24, 0.28, 0.32, 0.36, 0.48, 0.56, 0.04, 0.28, 0.48, 0.00, 0.16, 0.40, 0.40, 0.52, 0.08, 0.20, 0.28, 0.40, 0.52, 0.16, 0.20, 0.36, 0.48, 0.52, 0.00, 0.20, 0.40, 0.52, 0.16, 0.36, 0.04, 0.24, 0.36, 0.44, 0.00, 0.20, 0.48, 0.60, 0.20, 0.56, 0.20, 0.28, 0.36, 0.48], \"tokens\":[\" GOD\", \" AS\", \" IT\", \" IS\", \" A\", \" DIRECT\", \" CONSEQUENCE\", \" CONSEQUENCE\", \" OF\", \" THIS\", \" OF\", \" THE\", \" SIN\", \" WHICH\", \" WHICH\", \" MAN\", \" THUS\", \" PUT\", \" PUNISH\", \"ED\", \" HAD\", \" GIVEN\", \" HER\", \" GIVEN\", \" HER\", \" A\", \" LOVELY\", \" LOVELY\", \" CHILD\", \" WHOSE\", \" PLACE\", \" PLACE\", \" WAS\", \" ON\", \" ON\", \" THAT\", \" SAME\", \" DAM\", \"E\", \" DISH\", \"ON\", \"OR\", \"ED\", \"ARD\", \"ED\", \" BO\", \"S\", \"O\", \"M\", \" TO\", \" TO\", \" CONNECT\", \" HER\", \" PAIR\", \" PARENT\", \" FOR\", \" EVER\", \" WITH\", \" HER\", \" WITH\", \" THE\", \" RACE\", \" A\", \"CE\", \" AND\", \" DE\", \"S\", \"CENT\", \"MENT\", \" OF\", \" MORTAL\", \" MORTAL\", \"S\", \" AND\", \" AND\", \" TO\", \" BE\", \" FINALLY\", \" FINALLY\", \" A\", \" BLESS\", \" LESS\", \" SOUL\", \" I\", \"LL\", \" IN\", \" HEAVEN\"]}\n",
            "\n",
            "./sherpa-onnx-en-wenet-gigaspeech/test_wavs/8k.wav\n",
            "Elapsed seconds: 2.6, Real time factor (RTF): 0.53\n",
            " YET THESE THOUGHTS THOUGHTS AFFECTED AFFECTED HESTER P PRIN PRIN LESS WITH WITH HOPE THAN APPREHENREHENSION\n",
            "{\"is_final\":false, \"segment\":0, \"start_time\":0.00, \"text\": \" YET THESE THOUGHTS THOUGHTS AFFECTED AFFECTED HESTER P PRIN PRIN LESS WITH WITH HOPE THAN APPREHENREHENSION\", \"timestamps\": [0.40, 0.00, 0.16, 0.36, 0.04, 0.24, 0.40, 0.56, 0.04, 0.08, 0.12, 0.32, 0.36, 0.00, 0.16, 0.36, 0.52, 0.36, 0.52, 0.00, 0.08, 0.20, 0.28, 0.40, 0.48], \"tokens\":[\" YET\", \" THESE\", \" THOUGHTS\", \" THOUGHTS\", \" AFFECTED\", \" AFFECTED\", \" HE\", \"STER\", \" P\", \" PRI\", \"N\", \" PRI\", \"N\", \" LESS\", \" WITH\", \" WITH\", \" HOPE\", \" THAN\", \" APP\", \"RE\", \"HEN\", \"RE\", \"HEN\", \"S\", \"ION\"]}\n",
            "\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "## Non-streaming decoding"
      ],
      "metadata": {
        "id": "PJP03ii1NgAE"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# float32 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx-offline \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-en-wenet-gigaspeech/model.onnx \\\n",
        "  --tokens=./sherpa-onnx-en-wenet-gigaspeech/tokens.txt \\\n",
        "  ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "IRKZJTFCNQRx",
        "outputId": "74ae79cd-d2f9-418c-a618-409451c2095c"
      },
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx-offline --wenet-ctc-model=./sherpa-onnx-en-wenet-gigaspeech/model.onnx --tokens=./sherpa-onnx-en-wenet-gigaspeech/tokens.txt ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/0.wav ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/1.wav ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/8k.wav \n",
            "\n",
            "OfflineRecognizerConfig(feat_config=OfflineFeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename=\"\", decoder_filename=\"\", joiner_filename=\"\"), paraformer=OfflineParaformerModelConfig(model=\"\"), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=\"\"), whisper=OfflineWhisperModelConfig(encoder=\"\", decoder=\"\", language=\"\", task=\"transcribe\"), tdnn=OfflineTdnnModelConfig(model=\"\"), zipformer_ctc=OfflineZipformerCtcModelConfig(model=\"\"), wenet_ctc=OfflineWenetCtcModelConfig(model=\"./sherpa-onnx-en-wenet-gigaspeech/model.onnx\"), tokens=\"./sherpa-onnx-en-wenet-gigaspeech/tokens.txt\", num_threads=2, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OfflineLMConfig(model=\"\", scale=0.5), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph=\"\", max_active=3000), decoding_method=\"greedy_search\", max_active_paths=4, hotwords_file=\"\", hotwords_score=1.5)\n",
            "Creating recognizer ...\n",
            "Started\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/offline-stream.cc:AcceptWaveformImpl:113 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "Done!\n",
            "\n",
            "./sherpa-onnx-en-wenet-gigaspeech/test_wavs/0.wav\n",
            "{\"text\": \" AFTER EARLY NIGHTFALL THE YELLOW LAMPS WOULD LIGHT UP HERE AND THERE THE SQUALID QUARTER OF THE BROTHELS\", \"timestamps\": [0.60, 0.96, 1.38, 1.62, 1.74, 1.98, 2.10, 2.40, 2.64, 2.82, 3.00, 3.24, 3.54, 3.72, 3.96, 4.32, 4.50, 4.62, 4.74, 4.86, 5.10, 5.46, 5.58, 5.76, 5.94, 6.12, 6.18], \"tokens\":[\" AFTER\", \" EARLY\", \" NIGHT\", \"FA\", \"LL\", \" THE\", \" YELLOW\", \" LAMP\", \"S\", \" WOULD\", \" LIGHT\", \" UP\", \" HERE\", \" AND\", \" THERE\", \" THE\", \" S\", \"QUA\", \"LI\", \"D\", \" QUARTER\", \" OF\", \" THE\", \" BRO\", \"T\", \"HEL\", \"S\"]}\n",
            "----\n",
            "./sherpa-onnx-en-wenet-gigaspeech/test_wavs/1.wav\n",
            "{\"text\": \" GOD AS A DIRECT CONSEQUENCE OF THE SIN WHICH MAN THUS PUNISHED HAD GIVEN HER A LOVELY CHILD WHOSE PLACE WAS ON THAT SAME DISHONORED BOSOM TO CONNECT HER PARENT FOR EVER WITH THE RACE AND DESCENT OF MORTALS AND TO BE FINALLY A BLESSED SOUL IN HEAVEN\", \"timestamps\": [0.54, 0.90, 1.02, 1.32, 1.62, 2.28, 2.40, 2.64, 2.88, 3.12, 3.42, 3.72, 4.02, 4.44, 4.68, 4.98, 5.22, 5.40, 5.88, 6.48, 6.84, 7.20, 7.38, 7.62, 7.86, 8.22, 8.46, 8.58, 8.70, 8.82, 8.88, 9.00, 9.12, 9.36, 9.66, 9.90, 10.20, 10.86, 11.04, 11.28, 11.46, 11.70, 12.06, 12.24, 12.30, 12.48, 12.72, 12.96, 13.32, 13.80, 13.98, 14.10, 14.34, 14.82, 15.00, 15.24, 15.54, 15.90, 16.08], \"tokens\":[\" GOD\", \" AS\", \" A\", \" DIRECT\", \" CONSEQUENCE\", \" OF\", \" THE\", \" SIN\", \" WHICH\", \" MAN\", \" THUS\", \" PUNISH\", \"ED\", \" HAD\", \" GIVEN\", \" HER\", \" A\", \" LOVELY\", \" CHILD\", \" WHOSE\", \" PLACE\", \" WAS\", \" ON\", \" THAT\", \" SAME\", \" DISH\", \"ON\", \"OR\", \"ED\", \" BO\", \"S\", \"O\", \"M\", \" TO\", \" CONNECT\", \" HER\", \" PARENT\", \" FOR\", \" EVER\", \" WITH\", \" THE\", \" RACE\", \" AND\", \" DE\", \"S\", \"CENT\", \" OF\", \" MORTAL\", \"S\", \" AND\", \" TO\", \" BE\", \" FINALLY\", \" A\", \" BLESS\", \"ED\", \" SOUL\", \" IN\", \" HEAVEN\"]}\n",
            "----\n",
            "./sherpa-onnx-en-wenet-gigaspeech/test_wavs/8k.wav\n",
            "{\"text\": \" YET THESE THOUGHTS AFFECTED HESTER PRYNE LESS WITH HOPE THAN APPREHENSION\", \"timestamps\": [0.60, 0.84, 1.14, 1.56, 1.86, 2.10, 2.28, 2.34, 2.46, 2.70, 3.06, 3.30, 3.72, 3.96, 4.14, 4.26, 4.44, 4.56], \"tokens\":[\" YET\", \" THESE\", \" THOUGHTS\", \" AFFECTED\", \" HE\", \"STER\", \" P\", \"RY\", \"NE\", \" LESS\", \" WITH\", \" HOPE\", \" THAN\", \" APP\", \"RE\", \"HEN\", \"S\", \"ION\"]}\n",
            "----\n",
            "num threads: 2\n",
            "decoding method: greedy_search\n",
            "Elapsed seconds: 2.838 s\n",
            "Real time factor (RTF): 2.838 / 28.165 = 0.101\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "%%shell\n",
        "# int8 models\n",
        "./sherpa-onnx/build/bin/sherpa-onnx-offline \\\n",
        "  --wenet-ctc-model=./sherpa-onnx-en-wenet-gigaspeech/model.int8.onnx \\\n",
        "  --tokens=./sherpa-onnx-en-wenet-gigaspeech/tokens.txt \\\n",
        "  ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/0.wav \\\n",
        "  ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/1.wav \\\n",
        "  ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/8k.wav"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "uqjsHuKEOTaA",
        "outputId": "43570311-c8fe-45be-ff67-64fdeb403547"
      },
      "execution_count": 31,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "/content/sherpa-onnx/sherpa-onnx/csrc/parse-options.cc:Read:361 ./sherpa-onnx/build/bin/sherpa-onnx-offline --wenet-ctc-model=./sherpa-onnx-en-wenet-gigaspeech/model.int8.onnx --tokens=./sherpa-onnx-en-wenet-gigaspeech/tokens.txt ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/0.wav ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/1.wav ./sherpa-onnx-en-wenet-gigaspeech/test_wavs/8k.wav \n",
            "\n",
            "OfflineRecognizerConfig(feat_config=OfflineFeatureExtractorConfig(sampling_rate=16000, feature_dim=80), model_config=OfflineModelConfig(transducer=OfflineTransducerModelConfig(encoder_filename=\"\", decoder_filename=\"\", joiner_filename=\"\"), paraformer=OfflineParaformerModelConfig(model=\"\"), nemo_ctc=OfflineNemoEncDecCtcModelConfig(model=\"\"), whisper=OfflineWhisperModelConfig(encoder=\"\", decoder=\"\", language=\"\", task=\"transcribe\"), tdnn=OfflineTdnnModelConfig(model=\"\"), zipformer_ctc=OfflineZipformerCtcModelConfig(model=\"\"), wenet_ctc=OfflineWenetCtcModelConfig(model=\"./sherpa-onnx-en-wenet-gigaspeech/model.int8.onnx\"), tokens=\"./sherpa-onnx-en-wenet-gigaspeech/tokens.txt\", num_threads=2, debug=False, provider=\"cpu\", model_type=\"\"), lm_config=OfflineLMConfig(model=\"\", scale=0.5), ctc_fst_decoder_config=OfflineCtcFstDecoderConfig(graph=\"\", max_active=3000), decoding_method=\"greedy_search\", max_active_paths=4, hotwords_file=\"\", hotwords_score=1.5)\n",
            "Creating recognizer ...\n",
            "Started\n",
            "/content/sherpa-onnx/sherpa-onnx/csrc/offline-stream.cc:AcceptWaveformImpl:113 Creating a resampler:\n",
            "   in_sample_rate: 8000\n",
            "   output_sample_rate: 16000\n",
            "\n",
            "Done!\n",
            "\n",
            "./sherpa-onnx-en-wenet-gigaspeech/test_wavs/0.wav\n",
            "{\"text\": \" AFTER EARLY NIGHTFALL THE YELLOW LAMPS WOULD LIGHT UP HERE AND THERE THE SQUALID QUARTER OF THE BROTHELS\", \"timestamps\": [0.60, 0.96, 1.38, 1.62, 1.74, 1.98, 2.10, 2.40, 2.64, 2.82, 3.00, 3.24, 3.54, 3.72, 3.96, 4.32, 4.50, 4.62, 4.74, 4.86, 5.10, 5.46, 5.58, 5.76, 5.94, 6.12, 6.18], \"tokens\":[\" AFTER\", \" EARLY\", \" NIGHT\", \"FA\", \"LL\", \" THE\", \" YELLOW\", \" LAMP\", \"S\", \" WOULD\", \" LIGHT\", \" UP\", \" HERE\", \" AND\", \" THERE\", \" THE\", \" S\", \"QUA\", \"LI\", \"D\", \" QUARTER\", \" OF\", \" THE\", \" BRO\", \"T\", \"HEL\", \"S\"]}\n",
            "----\n",
            "./sherpa-onnx-en-wenet-gigaspeech/test_wavs/1.wav\n",
            "{\"text\": \" GOD AS A DIRECT CONSEQUENCE OF THE SIN WHICH MAN THUS PUNISHED HAD GIVEN HER A LOVELY CHILD WHOSE PLACE WAS ON THAT SAME DISHONORED BOSOM TO CONNECT HER PARENT FOR EVER WITH THE RACE AND DESCENT OF MORTALS AND TO BE FINALLY A BLESSED SOUL IN HEAVEN\", \"timestamps\": [0.54, 0.90, 1.08, 1.32, 1.62, 2.28, 2.40, 2.64, 2.88, 3.12, 3.42, 3.72, 4.02, 4.44, 4.68, 4.98, 5.22, 5.40, 5.88, 6.48, 6.84, 7.20, 7.38, 7.62, 7.92, 8.22, 8.46, 8.58, 8.70, 8.82, 8.88, 9.00, 9.12, 9.36, 9.66, 9.90, 10.20, 10.86, 11.04, 11.28, 11.46, 11.70, 12.06, 12.24, 12.30, 12.48, 12.72, 12.96, 13.32, 13.80, 13.98, 14.10, 14.34, 14.82, 15.00, 15.24, 15.60, 15.90, 16.08], \"tokens\":[\" GOD\", \" AS\", \" A\", \" DIRECT\", \" CONSEQUENCE\", \" OF\", \" THE\", \" SIN\", \" WHICH\", \" MAN\", \" THUS\", \" PUNISH\", \"ED\", \" HAD\", \" GIVEN\", \" HER\", \" A\", \" LOVELY\", \" CHILD\", \" WHOSE\", \" PLACE\", \" WAS\", \" ON\", \" THAT\", \" SAME\", \" DISH\", \"ON\", \"OR\", \"ED\", \" BO\", \"S\", \"O\", \"M\", \" TO\", \" CONNECT\", \" HER\", \" PARENT\", \" FOR\", \" EVER\", \" WITH\", \" THE\", \" RACE\", \" AND\", \" DE\", \"S\", \"CENT\", \" OF\", \" MORTAL\", \"S\", \" AND\", \" TO\", \" BE\", \" FINALLY\", \" A\", \" BLESS\", \"ED\", \" SOUL\", \" IN\", \" HEAVEN\"]}\n",
            "----\n",
            "./sherpa-onnx-en-wenet-gigaspeech/test_wavs/8k.wav\n",
            "{\"text\": \" YET THESE THOUGHTS AFFECTED HESTER PRYNE LESS WITH HOPE THAN APPREHENSION\", \"timestamps\": [0.60, 0.84, 1.14, 1.56, 1.92, 2.10, 2.28, 2.34, 2.46, 2.70, 3.06, 3.30, 3.72, 3.96, 4.14, 4.26, 4.44, 4.56], \"tokens\":[\" YET\", \" THESE\", \" THOUGHTS\", \" AFFECTED\", \" HE\", \"STER\", \" P\", \"RY\", \"NE\", \" LESS\", \" WITH\", \" HOPE\", \" THAN\", \" APP\", \"RE\", \"HEN\", \"S\", \"ION\"]}\n",
            "----\n",
            "num threads: 2\n",
            "decoding method: greedy_search\n",
            "Elapsed seconds: 3.639 s\n",
            "Real time factor (RTF): 3.639 / 28.165 = 0.129\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": []
          },
          "metadata": {},
          "execution_count": 31
        }
      ]
    }
  ]
}