Áudio
whispering-ui
Native desktop UI for live Whisper transcription and translation.
★ 329 estrelasMIT
Ver o guia →// audio · collabora/WhisperLive
WhisperLive
WhisperLive é um projeto de áudio de código aberto de collabora (collabora/WhisperLive no GitHub). Tem 4.309 estrelas no GitHub e 603 forks, é publicado sob a licença MIT e foi atualizado pela última vez no GitHub em 7 de outubro de 2026.
WhisperLive: a nearly-live OpenAI Whisper transcription server for files, mics, and streams
★ 4,3 mil estrelas⑂ 603 forksMITatualizado out 2026
▦ visual: o README deste projeto não inclui nenhuma captura incorporável,
então aqui vai um marcador. O guia abaixo está completo mesmo assim.
então aqui vai um marcador. O guia abaixo está completo mesmo assim.
// dados do projeto
Dados do projeto
- Repositório
- collabora/WhisperLive
- Estrelas no GitHub
- 4.309
- Forks
- 603
- Licença
- MIT
- Última atualização no GitHub
- 7 de outubro de 2026
- Categoria
- Áudio
- Tipo de ficha
- Guia de instalação completo
// como funciona
Como funciona
- Plan your deployment
Decide which backend fits your hardware — faster-whisper (default), TensorRT, or OpenVINO — and your client types.
- Install
Run the setup script for PortAudio, create a Python 3.12 environment, and pip-install whisper-live.
- Start the server
Launch run_server.py on a port with your client and connection limits.
- Transcribe something
Send a file with the client script, or use the Python TranscriptionClient from your own code.
// recursos
Por que as pessoas gostam tanto
Multiple inference backends
faster-whisper, TensorRT, and OpenVINO backends for different hardware.
Rich transcription output
Word-level timestamps and confidence scores, not just plain text.
Speaker diarization
Optional diarization via pyannote.audio identifies who spoke when.
Hotwords and vocabulary
Bias recognition toward custom terms and names.
Flexible inputs
Transcribe files, live microphone input, raw PCM, and RTSP/HLS streams; batch inference is supported.
OpenAI-compatible REST option
An --enable_rest flag exposes an OpenAI-style transcription API alongside the streaming protocol.
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// execute você mesmo
Execute você mesmo
- Clone the repository
Clone the project and enter its directory.
git clone https://github.com/collabora/WhisperLive.git cd WhisperLive - Install
Install system audio dependencies, then the Python package (in a Python 3.12 venv).
bash scripts/setup.sh pip install whisper-live - Start the server
Run the transcription server with the faster-whisper backend.
python3 run_server.py --port 9090 --backend faster_whisper --max_clients 4 --max_connection_time 600
// casos de uso
O que você pode criar
- Transcribe live meetings or lectures with word-level timestamps
- Add speech-to-text to an app without sending audio to a cloud API
- Transcribe RTSP camera or broadcast streams in near real time
- Batch-transcribe a folder of interviews with speaker labels
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// perguntas frequentes
Perguntas frequentes
Who maintains WhisperLive?
Collabora, the open-source consultancy, maintains WhisperLive.
Is WhisperLive free?
Yes, MIT-licensed; Whisper models run locally on your hardware.
Does it need a paid API key?
No cloud key is needed. Optional speaker diarization uses pyannote.audio models from Hugging Face, which may require accepting model terms there.
How does it compare to OpenAI's Whisper API?
The API is a managed per-minute service; WhisperLive is a self-hosted streaming server with multiple local backends, diarization, and stream inputs.
How do I get started?
Run `bash scripts/setup.sh`, `pip install whisper-live`, start `run_server.py`, then send audio with `run_client.py --files <file>`.
// continue explorando
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Ver o guia →// alternativas
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// mais em audio
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Baixe o WhisperLive
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