ref ggerganov#4 : added transcription timestamps

Can be turned off with "-nt" argument.
Performance has also improved.

README.md

@@ -31,7 +31,7 @@ $ make base.en
 
 gcc -pthread -O3 -mavx -mavx2 -mfma -mf16c -c ggml.c
 g++ -pthread -O3 -std=c++11 -c main.cpp
-g++ -o main ggml.o main.o
+g++ -pthread -o main ggml.o main.o
 ./main -h
 
 usage: ./main [options]
@@ -40,22 +40,17 @@ options:
   -h,       --help           show this help message and exit
   -s SEED,  --seed SEED      RNG seed (default: -1)
   -t N,     --threads N      number of threads to use during computation (default: 4)
-  -T N,     --tokens N       maximum number of tokens to generate per iteration (default: 64)
   -v,       --verbose        verbose output
             --translate      translate from source language to english
   -ps,      --print_special  print special tokens
+  -nt,      --no_timestamps  do not print timestamps
   -l LANG,  --language LANG  spoken language (default: en)
   -m FNAME, --model FNAME    model path (default: models/ggml-base.en.bin)
   -f FNAME, --file FNAME     input WAV file path (default: samples/jfk.wav)
 
 bash ./download-ggml-model.sh base.en
 Downloading ggml model base.en ...
-models/ggml-base.en.bin         100%[=====================================>] 141.11M  7.84MB/s    in 18s
-Done! Model 'base.en' saved in 'models/ggml-base.en.bin'
-You can now use it like this:
-
-  $ ./main -m models/ggml-base.en.bin -f samples/jfk.wav
-
+Model base.en already exists. Skipping download.
 
 ===============================================
 Running base.en on all samples in ./samples ...
@@ -86,16 +81,17 @@ whisper_model_load: model size  =   140.54 MB
 log_mel_spectrogram: n_sample = 176000, n_len = 1100
 log_mel_spectrogram: recording length: 11.000000 s
 
-main: processing 176000 samples (11.0 sec), 4 threads, lang = english, task = transcribe ...
+main: processing 176000 samples (11.0 sec), 4 threads, lang = english, task = transcribe, timestamps = 1 ...
 
- And so my fellow Americans ask not what your country can do for you. Ask what you can do for your country.
+[00:00.000 --> 00:11.000]   And so my fellow Americans ask not what your country can do for you. Ask what you can do for your country.
 
-main:     load time =    71.89 ms
-main:      mel time =    36.95 ms
+
+main:     load time =    61.78 ms
+main:      mel time =    41.74 ms
 main:   sample time =     2.10 ms
-main:   encode time =   700.94 ms / 116.82 ms per layer
-main:   decode time =    86.14 ms
-main:    total time =   898.72 ms
+main:   encode time =   718.60 ms / 119.77 ms per layer
+main:   decode time =    83.55 ms
+main:    total time =   908.15 ms
 ```
 
 The command downloads the `base.en` model converted to custom `ggml` format and runs the inference on all `.wav` samples in the folder `samples`.
@@ -131,10 +127,73 @@ For example, you can use `ffmpeg` like this:
 ffmpeg -i input.mp3 -ar 16000 -ac 1 -c:a pcm_s16le output.wav
 ```
 
+Here is another example of transcribing a [3:24 min speech](https://upload.wikimedia.org/wikipedia/commons/1/1f/George_W_Bush_Columbia_FINAL.ogg) in less than a minute, using `medium.en` model:
+
+```bash
+$ ./main -m models/ggml-medium.en.bin -f samples/gb1.wav -t 8
+whisper_model_load: loading model from 'models/ggml-medium.en.bin'
+whisper_model_load: n_vocab       = 51864
+whisper_model_load: n_audio_ctx   = 1500
+whisper_model_load: n_audio_state = 1024
+whisper_model_load: n_audio_head  = 16
+whisper_model_load: n_audio_layer = 24
+whisper_model_load: n_text_ctx    = 448
+whisper_model_load: n_text_state  = 1024
+whisper_model_load: n_text_head   = 16
+whisper_model_load: n_text_layer  = 24
+whisper_model_load: n_mels        = 80
+whisper_model_load: f16           = 1
+whisper_model_load: type          = 4
+whisper_model_load: mem_required  = 2786.00 MB
+whisper_model_load: adding 1607 extra tokens
+whisper_model_load: ggml ctx size = 1644.97 MB
+whisper_model_load: memory size =   182.62 MB
+whisper_model_load: model size  =  1462.12 MB
+log_mel_spectrogram: n_sample = 3179750, n_len = 19873
+log_mel_spectrogram: recording length: 198.734375 s
+
+main: processing 3179750 samples (198.7 sec), 8 threads, lang = english, task = transcribe, timestamps = 1 ...
+
+[00:00.000 --> 00:08.000]   My fellow Americans, this day has brought terrible news and great sadness to our country.
+[00:08.000 --> 00:17.000]   At 9 o'clock this morning, Mission Control in Houston lost contact with our Space Shuttle Columbia.
+[00:17.000 --> 00:24.000]   A short time later, debris was seen falling from the skies above Texas.
+[00:24.000 --> 00:29.000]   The Columbia's lost. There are no survivors.
+[00:29.000 --> 00:32.000]   On board was a crew of seven.
+[00:32.000 --> 00:43.000]   Colonel Rick Husband, Lieutenant Colonel Michael Anderson, Commander Laurel Clark, Captain David Brown, Commander William McCool,
+[00:43.000 --> 00:52.000]   Dr. Kultner Aschavla, and Elon Ramon, a Colonel in the Israeli Air Force.
+[00:52.000 --> 00:58.000]   These men and women assumed great risk in the service to all humanity.
+[00:58.000 --> 01:06.000]   In an age when space flight has come to seem almost routine, it is easy to overlook the dangers of travel by rocket
+[01:06.000 --> 01:12.000]   and the difficulties of navigating the fierce outer atmosphere of the Earth.
+[01:12.000 --> 01:22.000]   These astronauts knew the dangers, and they faced them willingly, knowing they had a high and noble purpose in life.
+[01:22.000 --> 01:30.000]   Because of their courage, endearing, and idealism, we will miss them all the more.
+[01:30.000 --> 01:40.000]   All Americans today are thinking as well of the families of these men and women who have been given this sudden shock and grief.
+[01:40.000 --> 01:45.000]   You're not alone. Our entire nation agrees with you.
+[01:45.000 --> 01:52.000]   And those you love will always have the respect and gratitude of this country.
+[01:52.000 --> 01:56.000]   The cause in which they died will continue.
+[01:56.000 --> 02:07.000]   Mankind is led into the darkness beyond our world by the inspiration of discovery and the longing to understand.
+[02:07.000 --> 02:11.000]   Our journey into space will go on.
+[02:11.000 --> 02:16.000]   In the skies today, we saw destruction and tragedy.
+[02:16.000 --> 02:22.000]   Yet farther than we can see, there is comfort and hope.
+[02:22.000 --> 02:31.000]   In the words of the prophet Isaiah, "Lift your eyes and look to the heavens who created all these.
+[02:31.000 --> 02:39.000]   He who brings out the starry hosts one by one and calls them each by name."
+[02:39.000 --> 02:46.000]   Because of his great power and mighty strength, not one of them is missing.
+[02:46.000 --> 02:55.000]   The same creator who names the stars also knows the names of the seven souls we mourn today.
+[02:55.000 --> 03:05.000]   The crew of the shuttle Columbia did not return safely to Earth, yet we can pray that all are safely home.
+[03:05.000 --> 03:14.000]   May God bless the grieving families and may God continue to bless America.
+[03:14.000 --> 03:24.000]   [Music]
+
+
+main:     load time =   438.55 ms
+main:      mel time =   440.22 ms
+main:   sample time =    32.23 ms
+main:   encode time = 42329.63 ms / 1763.73 ms per layer
+main:   decode time = 15190.00 ms
+main:    total time = 58444.63 ms
+```
+
 ## Limitations
 
 - Very basic greedy sampling scheme - always pick up the top token
-- No timestamps
 - Inference only
 - Runs on the CPU
 - Only mono-channel 16-bit WAV is supported