* Add Android sample
* Use main project C files
* Stop existing playback before starting new playback
* Make text scrollable
* Stop playback when starting to record
* Remove extra var
- Clear past prompt when there is very short audio left for processing.
My observation is that in these cases the decoding tends to repeat and
hallucinate stuff and I think this is induced by the existing prompt
- When we fail to sample timestamp token, retry by clearing the past
prompt. If it fails again, then we advance the window by 1 second
* npm : preparing infra for node package
* npm : package infra ready
* npm : initial version ready
* npm : change name to whisper.cpp
whisper.js is taken
Also added a small wrapper function to more safely read model data without having to get the sizeof right. I tested this on tiny, base and large models, there was no change in behaviour.
Do not allow for text segments to go beyond end of audio.
This partially mitigates some issues when the last audio window is 1-2
seconds just before the end of the audio file and the decoding spirals
into a repetition of the last transcribed phrase.
The old "large" model is now renamed "large-v1".
If you have been using it, make sure to rename it and download the new
"large" model for best results.
* whisper : try to improve the token sampling strategy
- Add the "max_initial_timestaamp" token logic from OpenAI
- Disallow sampling timestamps that are in the past
* whisper : fix the max initial timestamp logic + fallback decoding
Digipom