word-level timestamps

[eschmidbauer]

Hi, I really appreciate you sharing this implementation.
I found it to be very fast with accurate results.
I do not see word-level timestamps in the result. Are word level timestamps possible?

[guillaumekln]

Hi,

Word-level timestamps are currently not possible. They usually require extensions to the model that are not implemented at this time.

[tohe91]

Thank you for the amazing work on this!
It would be amazing if world level timestamps could be implemented in faster-whisper, once the world-level-timestamps branch is merged to main in whisper

[collynce]

Just checked out the whisper repo and world-level timestamp PR has been merged. I would be great indeed to have the same on faster-whiper.

Great work!

[guillaumekln]

I just pushed an experimental branch implementing word-level timestamps! It would be great if you can test this early.

Note that I implemented exactly the same logic as openai/whisper. So if there is a strange result and openai/whisper has the same result, you should report the issue to openai/whisper and not here.

Here's how you can test this today:

Install the development branch of faster-whisper

pip install --force-reinstall "faster-whisper[conversion] @ https://github.com/guillaumekln/faster-whisper/archive/refs/heads/word-level-timestamps.tar.gz"

Install the development build of CTranslate2

1. Go to this build page
2. Download the artifact "python-wheels"
3. Extract the archive
4. Install the wheel matching your system and Python version, for example:

pip install --force-reinstall ctranslate2-3.8.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl

Reconvert the model

The model should be converted again with the latest version of CTranslate2 as the configuration needs to be updated with additional information:

ct2-transformers-converter --model openai/whisper-large-v2 --output_dir whisper-large-v2-ct2 --copy_files tokenizer.json --quantization float16

Transcribe with word-level timestamps

segments, _ = model.transcribe(audio_path, word_timestamps=True)

for segment in segments:
    print(segment.words)

[eschmidbauer]

just tested this with the tiny model and it worked!
going to do more tests but this is great, thanks so much for sharing!

[eschmidbauer]

large-v2 seems to work too. Thanks again

[Jeronymous]

When I tested word timestamps on a bunch of file, I saw this error happening on some corner case:

  File "/usr/local/lib/python3.10/site-packages/faster_whisper/transcribe.py", line 531, in add_word_timestamps
    alignment = self.find_alignment(tokenizer, text_tokens, mel, num_frames)
  File "/usr/local/lib/python3.10/site-packages/faster_whisper/transcribe.py", line 598, in find_alignment
    start_times = jump_times[word_boundaries[:-1]]
IndexError: index 1 is out of bounds for axis 0 with size 1

[guillaumekln]

Thank you for testing!

Do you confirm the same file works without issue in openai/whisper? If yes, is it possible for you to share this input file?