Áudio
whispering-ui
Native desktop UI for live Whisper transcription and translation.
★ 329 estrelasMIT
Ver o guia →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
Decide which backend fits your hardware — faster-whisper (default), TensorRT, or OpenVINO — and your client types.
Run the setup script for PortAudio, create a Python 3.12 environment, and pip-install whisper-live.
Launch run_server.py on a port with your client and connection limits.
Send a file with the client script, or use the Python TranscriptionClient from your own code.
faster-whisper, TensorRT, and OpenVINO backends for different hardware.
Word-level timestamps and confidence scores, not just plain text.
Optional diarization via pyannote.audio identifies who spoke when.
Bias recognition toward custom terms and names.
Transcribe files, live microphone input, raw PCM, and RTSP/HLS streams; batch inference is supported.
An --enable_rest flag exposes an OpenAI-style transcription API alongside the streaming protocol.
Clone the project and enter its directory.
git clone https://github.com/collabora/WhisperLive.git
cd WhisperLiveInstall system audio dependencies, then the Python package (in a Python 3.12 venv).
bash scripts/setup.sh
pip install whisper-liveRun the transcription server with the faster-whisper backend.
python3 run_server.py --port 9090 --backend faster_whisper --max_clients 4 --max_connection_time 600Collabora, the open-source consultancy, maintains WhisperLive.
Yes, MIT-licensed; Whisper models run locally on your hardware.
No cloud key is needed. Optional speaker diarization uses pyannote.audio models from Hugging Face, which may require accepting model terms there.
The API is a managed per-minute service; WhisperLive is a self-hosted streaming server with multiple local backends, diarization, and stream inputs.
Run `bash scripts/setup.sh`, `pip install whisper-live`, start `run_server.py`, then send audio with `run_client.py --files <file>`.
Native desktop UI for live Whisper transcription and translation.
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Automatic Speech Recognition with Speaker Diarization based on OpenAI Whisper
Port of OpenAI's Whisper model in C/C++
Os outros projetos de Áudio com mais estrelas no catálogo do LibreAI — a lista realista de alternativas se WhisperLive não for o ideal para você.
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Port of OpenAI's Whisper model in C/C++
Projetos de Áudio próximos no catálogo, os mais próximos em estrelas de WhisperLive: continue explorando dos dois lados dele.
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Grátis e aberto: pegue o código-fonte, dê uma estrela no repositório e comece a criar.