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Fedir Zadniprovskyi
rename to `speaches`
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!!! note

This project was previously named `faster-whisper-server`. I've decided to change the name from `faster-whisper-server`, as the project has evolved to support more than just transcription.

!!! note

These docs are a work in progress. If you have any questions, suggestions, or find a bug, please create an issue.

TODO: add HuggingFace Space URL

Speaches

speaches is an OpenAI API-compatible server supporting transcription, translation, and speech generation. For transcription/translation it uses faster-whisper and for text-to-speech piper is used.

Features:

  • GPU and CPU support.
  • Deployable via Docker Compose / Docker
  • Highly configurable
  • OpenAI API compatible. All tools and SDKs that work with OpenAI's API should work with speaches.
  • Streaming support (transcription is sent via SSE as the audio is transcribed. You don't need to wait for the audio to fully be transcribed before receiving it).
  • Live transcription support (audio is sent via websocket as it's generated).
  • Dynamic model loading / offloading. Just specify which model you want to use in the request and it will be loaded automatically. It will then be unloaded after a period of inactivity.
  • [Text-to-speech (TTS) via piper]
  • (Coming soon) Audio generation (chat completions endpoint) | OpenAI Documentation
    • Generate a spoken audio summary of a body of text (text in, audio out)
    • Perform sentiment analysis on a recording (audio in, text out)
    • Async speech to speech interactions with a model (audio in, audio out)
  • (Coming soon) Realtime API | OpenAI Documentation

Please create an issue if you find a bug, have a question, or a feature suggestion.

OpenAI API Compatibility ++

See OpenAI API reference for more information.

  • Audio file transcription via POST /v1/audio/transcriptions endpoint.
    • Unlike OpenAI's API, speaches also supports streaming transcriptions (and translations). This is useful for when you want to process large audio files and would rather receive the transcription in chunks as they are processed, rather than waiting for the whole file to be transcribed. It works similarly to chat messages when chatting with LLMs.
  • Audio file translation via POST /v1/audio/translations endpoint.
  • Live audio transcription via WS /v1/audio/transcriptions endpoint.
    • LocalAgreement2 (paper | original implementation) algorithm is used for live transcription.
    • Only transcription of a single channel, 16000 sample rate, raw, 16-bit little-endian audio is supported.

TODO: add a note about gradio ui TODO: add a note about hf space