Code for serving Meta's SeamlessM4T and OpenAI's Whisper via Beam and for running Voice Bot, a telegram bot to transform your voice notes into text.
- A Beam App to serve a serverless inference REST endpoint for speech models. Roughly, it receives a voice note's bytes and returns a transcript text.
- A Python Bot to let people send or forward voice notes and forward them in turn to the Beam App.
The app does not log, save, preprocess, or post process any user data, except for each user's preference of preferred language and model.
SeamlessM4T is a multilingual and multitask model that translates and transcribes across speech and text.
Whisper is a general-purpose speech recognition model. In this project, it is user for multilingual speech recognition and speech translation.
Useful Links
- SeamlessM4T Demo on HF: https://huggingface.co/spaces/facebook/seamless_m4t
- OpenAI's Whisper Demo on Beam: https://github.com/slai-labs/get-beam/blob/main/examples/whisper-tutorial/app.py
- We trim voice notes to a maximum of 60 seconds for SeamlessM4T and 240 seconds for Whisper.
- App gets suspended if not invoked for longer that 120 seconds. If that happens, then you'll cold start it and have to wait ~60 seconds to get your transcript.
- This is a side project, so
- code is not nice and tidy
- I can't guarantee 24/7 assistance
- I can't guarantee it'll be up forever