Áudio
joinly
Give AI agents a seat in your meetings.
★ 566 estrelasMIT
Ver o guia →docker-whisper é um projeto de áudio de código aberto de hwdsl2 (hwdsl2/docker-whisper no GitHub). Tem 112 estrelas no GitHub e 21 forks, é publicado sob a licença NOASSERTION e foi atualizado pela última vez no GitHub em 21 de setembro de 2026.
Self-hosted Whisper speech-to-text as a Docker image.
Decide what you want the project to do before installing anything.
Grab the source and skim the README for setup requirements.
Install dependencies and add any API keys or settings it needs.
Launch it and follow the example workflow from the docs.
Ships with container support for one-command self-hosting.
Deploy the full stack on your own infrastructure.
Turns spoken audio into accurate text.
Adapt the pipeline to your audio needs.
Cleans up background noise automatically.
Knows who said what in multi-speaker audio.
Download the source and move into the project folder.
git clone https://github.com/hwdsl2/docker-whisper.git
cd docker-whisperCreate a virtual environment and install the requirements.
python3 -m venv .venv && source .venv/bin/activate
pip install -r requirements.txtStart the app or CLI and follow the README examples.
python main.py --helpIt is an open-source project at hwdsl2/docker-whisper with 21 forks. Check the repo’s contributors and recent commits to judge how active maintenance is.
GitHub does not assert a license for this repo, so treat the code as all rights reserved until the author adds one.
MP3, WAV, and most common formats are supported.
It helps a lot for transcription speed, but CPU mode works too.
Tools with diarization label who said what.
Give AI agents a seat in your meetings.
Voice-to-text for the Linux terminal, from a hotkey.
NVIDIA Broadcast-style AI effects for Linux and macOS.
A ready API for speech-to-text with per-user access control.
Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text…
Open source voice AI platform. Self-hosted alternative to Vapi and Retell. On Prem, BYOK across Speech to Speech or LLM/STT/TTS, with a visual workflow build…
Os outros projetos de Áudio com mais estrelas no catálogo do LibreAI — a lista realista de alternativas se docker-whisper não for o ideal para você.
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1 min voice data can also be used to train a good TTS model! (few shot voice cloning)
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Grátis e aberto: pegue o código-fonte, dê uma estrela no repositório e comece a criar.