Audio
leon
🧠 Leon is your open-source personal assistant.
★ 17,6k estrellasMIT
Ver la guía →silero-models es un proyecto de audio de código abierto de snakers4 (snakers4/silero-models en GitHub). Tiene 6.125 estrellas en GitHub y 373 bifurcaciones, se publica bajo la licencia Custom y se actualizó por última vez en GitHub el 31 de julio de 2026.
Silero Models: pre-trained text-to-speech models made embarrassingly simple
Transcription, synthesis, voice changing, or editing — each tool here majors in one.
Binaries, pip packages, or Docker; models download on first run for AI tools.
Drop in a recording or type what you want spoken.
WAV/MP3/OGG outputs drop straight into editors or apps.
Many run fully on-device — nothing you say leaves the machine.
Open licenses let you ship voice features without per-minute API bills.
CLI and Python APIs slot into larger pipelines.
Dozens of languages supported, not just English.
Streaming transcription and TTS for live applications.
Tell speakers apart in meetings and interviews automatically.
Download the source and move into the project folder.
git clone https://github.com/snakers4/silero-models.git
cd silero-modelsEvery project documents its own setup; start with install requirements.
cat README.md | head -60Follow the project's launch command — Docker, pip, npm, or a binary release.
# see README for the exact launch commandIt is an open-source project at snakers4/silero-models with 373 forks. Check the repo's contributors and recent commits to see how active maintenance is.
Licensed under Custom — check the repo for commercial-use terms.
Check each license — many allow it, but voice-cloning has ethical and legal boundaries.
Whisper-class models rival paid services on clear audio; noisy recordings need cleanup first.
Dozens; English is strongest, major world languages are solid.
🧠 Leon is your open-source personal assistant.
A robust, efficient, low-latency speech-to-text library with advanced voice activity detection, wake word activation and instant transcription.
Automatic Speech Recognition with Speaker Diarization based on OpenAI Whisper
The easiest way to serve AI models, including speech-to-text, on Kubernetes.
Human-level text-to-speech through style diffusion and adversarial training with speech language models.
Instant, ultra-realistic text-to-speech from a simple local app.
Los demás proyectos de Audio con más estrellas del catálogo de LibreAI: la lista realista de alternativas si silero-models no es lo que buscas.
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++
Proyectos de Audio cercanos en el catálogo, los más próximos en estrellas a silero-models: sigue explorando a ambos lados.
Human-level text-to-speech through style diffusion and adversarial training with speech language models.
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…
On-device Speech AI for Apple Silicon
Fast and local neural text-to-speech engine
eSpeak NG — the compact open-source speech synthesizer for 100+ languages, small enough to embed anywhere.
Automatic Speech Recognition with Speaker Diarization based on OpenAI Whisper
Gratis y abierto: consigue el código fuente, dale una estrella al repositorio y empieza a crear.