https://github.com/speaches-ai/speaches

https://github.com/speaches-ai/speaches

docker docker-compose faster-whisper openai-api openai-whisper openai-whisper-translation transcription whisper whisper-ai

Last synced: about 4 hours ago
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• Host: GitHub
• URL: https://github.com/speaches-ai/speaches
• Owner: speaches-ai
• License: mit
• Created: 2024-05-18T02:26:20.000Z (8 months ago)
• Default Branch: master
• Last Pushed: 2025-01-12T02:22:52.000Z (1 day ago)
• Last Synced: 2025-01-12T02:36:52.665Z (1 day ago)
• Topics: docker, docker-compose, faster-whisper, openai-api, openai-whisper, openai-whisper-translation, transcription, whisper, whisper-ai
• Language: Python
• Homepage: https://speaches-ai.github.io/speaches/
• Size: 67.7 MB
• Stars: 988
• Watchers: 10
• Forks: 136
• Open Issues: 32
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
> [!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.

# Speaches

`speaches` is an OpenAI API-compatible server supporting streaming transcription, translation, and speech generation. Speach-to-Text is powered by [faster-whisper](https://github.com/SYSTRAN/faster-whisper) and for Text-to-Speech [piper](https://github.com/rhasspy/piper) and [Kokoro](https://huggingface.co/hexgrad/Kokoro-82M) are used. This project aims to be Ollama, but for TTS/STT models.

Try it out on the [HuggingFace Space](https://huggingface.co/spaces/speaches-ai/speaches)

See the documentation for installation instructions and usage: [https://speaches-ai.github.io/speaches/](https://speaches-ai.github.io/speaches/)

## Features:

- GPU and CPU support.

- [Deployable via Docker Compose / Docker](https://speaches-ai.github.io/speaches/installation/)

- [Highly configurable](https://speaches-ai.github.io/speaches/configuration/)

- 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).

  - LocalAgreement2 ([paper](https://aclanthology.org/2023.ijcnlp-demo.3.pdf) | [original implementation](https://github.com/ufal/whisper_streaming)) algorithm is used for live transcription.

- 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 via `kokoro`(Ranked #1 in the [TTS Arena](https://huggingface.co/spaces/Pendrokar/TTS-Spaces-Arena)) and `piper` models.

- [Coming soon](https://github.com/speaches-ai/speaches/issues/231): Audio generation (chat completions endpoint) | [OpenAI Documentation](https://platform.openai.com/docs/guides/realtime)

  - 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](https://github.com/speaches-ai/speaches/issues/115): Realtime API | [OpenAI Documentation](https://platform.openai.com/docs/guides/realtime)

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

## Demo

### Streaming Transcription

TODO

### Speech Generation

https://github.com/user-attachments/assets/0021acd9-f480-4bc3-904d-831f54c4d45b

### Live Transcription (using WebSockets)

https://github.com/fedirz/faster-whisper-server/assets/76551385/e334c124-af61-41d4-839c-874be150598f