Audio
whispering-ui
Native desktop UI for live Whisper transcription and translation.
★ 329 starsMIT
View guide →WhisperLive: a nearly-live OpenAI Whisper transcription server for files, mics, and streams
WhisperLive is an open-source audio project by collabora (collabora/WhisperLive on GitHub). It has 4,309 GitHub stars and 603 forks, is released under the MIT license, and was last updated on GitHub on 7 October 2026.
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.
AWS sample app for live meeting transcription and AI summaries.
Faster-Whisper-XXL-GUI — gui for faster‑whisper‑xxl transcription tool: download, open-...
Blazing-fast multi-backend Whisper transcription for any file or URL.
Automatic Speech Recognition with Speaker Diarization based on OpenAI Whisper
Port of OpenAI's Whisper model in C/C++
The most-starred other Audio projects in the LibreAI catalogue — the realistic shortlist if WhisperLive is not the right fit.
利用 AI 大模型和自动化工作流，根据主题或关键词一键生成高清短视频。Generate HD short videos from a topic or keyword with an automated AI workflow.
Robust Speech Recognition via Large-Scale Weak Supervision
1 min voice data can also be used to train a good TTS model! (few shot voice cloning)
Clone a voice from 5 seconds of audio and generate arbitrary speech in real time
Port of OpenAI's Whisper model in C/C++
Free and open — grab the source, star the repo, and start creating.