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LSTM-transducer-based Models

Hint

Please refer to install_sherpa_onnx to install sherpa-onnx before you read this section.

csukuangfj/sherpa-onnx-lstm-en-2023-02-17 (English)

This model trained using the GigaSpeech and the LibriSpeech dataset.

Please see k2-fsa/icefall#558 for how the model is trained.

You can find the training code at

https://github.com/k2-fsa/icefall/tree/master/egs/librispeech/ASR/lstm_transducer_stateless2

In the following, we describe how to download it and use it with sherpa-onnx.

Download the model

Please use the following commands to download it.

cd /path/to/sherpa-onnx

wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-lstm-en-2023-02-17.tar.bz2

# For Chinese users, please use the following mirror
# wget https://hub.nuaa.cf/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-lstm-en-2023-02-17.tar.bz2

tar xvf sherpa-onnx-lstm-en-2023-02-17.tar.bz2
rm sherpa-onnx-lstm-en-2023-02-17.tar.bz2

Please check that the file sizes of the pre-trained models are correct. See the file sizes of *.onnx files below.

sherpa-onnx-lstm-en-2023-02-17$ ls -lh *.onnx
-rw-r--r-- 1 kuangfangjun root  1.3M Mar 31 22:41 decoder-epoch-99-avg-1.int8.onnx
-rw-r--r-- 1 kuangfangjun root  2.0M Mar 31 22:41 decoder-epoch-99-avg-1.onnx
-rw-r--r-- 1 kuangfangjun root   80M Mar 31 22:41 encoder-epoch-99-avg-1.int8.onnx
-rw-r--r-- 1 kuangfangjun root  319M Mar 31 22:41 encoder-epoch-99-avg-1.onnx
-rw-r--r-- 1 kuangfangjun root  254K Mar 31 22:41 joiner-epoch-99-avg-1.int8.onnx
-rw-r--r-- 1 kuangfangjun root 1003K Mar 31 22:41 joiner-epoch-99-avg-1.onnx

Decode a single wave file

Hint

It supports decoding only wave files of a single channel with 16-bit encoded samples, while the sampling rate does not need to be 16 kHz.

fp32

The following code shows how to use fp32 models to decode a wave file:

cd /path/to/sherpa-onnx

./build/bin/sherpa-onnx \
  --tokens=./sherpa-onnx-lstm-en-2023-02-17/tokens.txt \
  --encoder=./sherpa-onnx-lstm-en-2023-02-17/encoder-epoch-99-avg-1.onnx \
  --decoder=./sherpa-onnx-lstm-en-2023-02-17/decoder-epoch-99-avg-1.onnx \
  --joiner=./sherpa-onnx-lstm-en-2023-02-17/joiner-epoch-99-avg-1.onnx \
  ./sherpa-onnx-lstm-en-2023-02-17/test_wavs/0.wav

Note

Please use ./build/bin/Release/sherpa-onnx.exe for Windows.

You should see the following output:

./code-lstm/sherpa-onnx-lstm-en-2023-02-17.txt

int8

The following code shows how to use int8 models to decode a wave file:

cd /path/to/sherpa-onnx

./build/bin/sherpa-onnx \
  --tokens=./sherpa-onnx-lstm-en-2023-02-17/tokens.txt \
  --encoder=./sherpa-onnx-lstm-en-2023-02-17/encoder-epoch-99-avg-1.int8.onnx \
  --decoder=./sherpa-onnx-lstm-en-2023-02-17/decoder-epoch-99-avg-1.int8.onnx \
  --joiner=./sherpa-onnx-lstm-en-2023-02-17/joiner-epoch-99-avg-1.int8.onnx \
  ./sherpa-onnx-lstm-en-2023-02-17/test_wavs/0.wav

Note

Please use ./build/bin/Release/sherpa-onnx.exe for Windows.

You should see the following output:

./code-lstm/sherpa-onnx-lstm-en-2023-02-17-int8.txt

Real-time speech recognition from a microphone

cd /path/to/sherpa-onnx

./build/bin/sherpa-onnx-microphone \
  --tokens=./sherpa-onnx-lstm-en-2023-02-17/tokens.txt \
  --encoder=./sherpa-onnx-lstm-en-2023-02-17/encoder-epoch-99-avg-1.onnx \
  --decoder=./sherpa-onnx-lstm-en-2023-02-17/decoder-epoch-99-avg-1.onnx \
  --joiner=./sherpa-onnx-lstm-en-2023-02-17/joiner-epoch-99-avg-1.onnx

Hint

If your system is Linux (including embedded Linux), you can also use sherpa-onnx-alsa to do real-time speech recognition with your microphone if sherpa-onnx-microphone does not work for you.

csukuangfj/sherpa-onnx-lstm-zh-2023-02-20 (Chinese)

This is a model trained using the WenetSpeech dataset.

Please see k2-fsa/icefall#595 for how the model is trained.

In the following, we describe how to download it and use it with sherpa-onnx.

Download the model

Please use the following commands to download it.

cd /path/to/sherpa-onnx

wget https://github.com/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-lstm-zh-2023-02-20.tar.bz2

# For Chinese users, you can use the following mirror
# wget https://hub.nuaa.cf/k2-fsa/sherpa-onnx/releases/download/asr-models/sherpa-onnx-lstm-zh-2023-02-20.tar.bz2

tar xvf sherpa-onnx-lstm-zh-2023-02-20.tar.bz2
rm sherpa-onnx-lstm-zh-2023-02-20.tar.bz2

Please check that the file sizes of the pre-trained models are correct. See the file sizes of *.onnx files below.

sherpa-onnx-lstm-zh-2023-02-20$ ls -lh *.onnx
-rw-r--r-- 1 kuangfangjun root  12M Mar 31 20:55 decoder-epoch-11-avg-1.int8.onnx
-rw-r--r-- 1 kuangfangjun root  12M Mar 31 20:55 decoder-epoch-11-avg-1.onnx
-rw-r--r-- 1 kuangfangjun root  80M Mar 31 20:55 encoder-epoch-11-avg-1.int8.onnx
-rw-r--r-- 1 kuangfangjun root 319M Mar 31 20:55 encoder-epoch-11-avg-1.onnx
-rw-r--r-- 1 kuangfangjun root 2.8M Mar 31 20:55 joiner-epoch-11-avg-1.int8.onnx
-rw-r--r-- 1 kuangfangjun root  11M Mar 31 20:55 joiner-epoch-11-avg-1.onnx

Decode a single wave file

Hint

It supports decoding only wave files of a single channel with 16-bit encoded samples, while the sampling rate does not need to be 16 kHz.

fp32

The following code shows how to use fp32 models to decode a wave file:

cd /path/to/sherpa-onnx

./build/bin/sherpa-onnx \
  --tokens=./sherpa-onnx-lstm-zh-2023-02-20/tokens.txt \
  --encoder=./sherpa-onnx-lstm-zh-2023-02-20/encoder-epoch-11-avg-1.onnx \
  --decoder=./sherpa-onnx-lstm-zh-2023-02-20/decoder-epoch-11-avg-1.onnx \
  --joiner=./sherpa-onnx-lstm-zh-2023-02-20/joiner-epoch-11-avg-1.onnx \
  ./sherpa-onnx-lstm-zh-2023-02-20/test_wavs/0.wav

Note

Please use ./build/bin/Release/sherpa-onnx.exe for Windows.

Caution

If you use Windows and get encoding issues, please run:

CHCP 65001

in your commandline.

You should see the following output:

./code-lstm/sherpa-onnx-lstm-zh-2023-02-20.txt

int8

The following code shows how to use int8 models to decode a wave file:

cd /path/to/sherpa-onnx

./build/bin/sherpa-onnx \
  --tokens=./sherpa-onnx-lstm-zh-2023-02-20/tokens.txt \
  --encoder=./sherpa-onnx-lstm-zh-2023-02-20/encoder-epoch-11-avg-1.int8.onnx \
  --decoder=./sherpa-onnx-lstm-zh-2023-02-20/decoder-epoch-11-avg-1.int8.onnx \
  --joiner=./sherpa-onnx-lstm-zh-2023-02-20/joiner-epoch-11-avg-1.int8.onnx \
  ./sherpa-onnx-lstm-zh-2023-02-20/test_wavs/0.wav

Note

Please use ./build/bin/Release/sherpa-onnx.exe for Windows.

Caution

If you use Windows and get encoding issues, please run:

CHCP 65001

in your commandline.

You should see the following output:

./code-lstm/sherpa-onnx-lstm-zh-2023-02-20-int8.txt

Real-time speech recognition from a microphone

cd /path/to/sherpa-onnx

./build/bin/sherpa-onnx-microphone \
  --tokens=./sherpa-onnx-lstm-zh-2023-02-20/tokens.txt \
  --encoder=./sherpa-onnx-lstm-zh-2023-02-20/encoder-epoch-11-avg-1.onnx \
  --decoder=./sherpa-onnx-lstm-zh-2023-02-20/decoder-epoch-11-avg-1.onnx \
  --joiner=./sherpa-onnx-lstm-zh-2023-02-20/joiner-epoch-11-avg-1.onnx

Hint

If your system is Linux (including embedded Linux), you can also use sherpa-onnx-alsa to do real-time speech recognition with your microphone if sherpa-onnx-microphone does not work for you.