Audio
ODS
ODS V3 Pre-Release: Public testing and refinement ahead of the official V3 launch. Turn your PC, Mac, or Linux box into a private AI server.
★ 7,0 Tsd. SterneApache-2.0
Anleitung ansehen →espnet ist ein Open-Source-Projekt aus der Kategorie Audio von espnet (espnet/espnet auf GitHub). Es hat 9.976 Sterne auf GitHub und 2.440 Forks, wird unter der Lizenz Apache-2.0 veröffentlicht und wurde zuletzt am 2. Oktober 2026 auf GitHub aktualisiert.
End-to-End Speech Processing Toolkit
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.
Neural models do the heavy lifting behind a simple interface.
Streaming transcription and TTS for live applications.
Tell speakers apart in meetings and interviews automatically.
Clone a voice from a short sample for narration and dubbing.
Whisper-grade transcription and natural neural voices, free.
Many run fully on-device — nothing you say leaves the machine.
Download the source and move into the project folder.
git clone https://github.com/espnet/espnet.git
cd espnetEvery 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 espnet/espnet with 2,440 forks. Check the repo's contributors and recent commits to see how active maintenance is.
Apache 2.0 licensed — commercial use allowed with attribution.
Whisper-class models rival paid services on clear audio; noisy recordings need cleanup first.
Dozens; English is strongest, major world languages are solid.
Most of these run fully offline after the model download.
ODS V3 Pre-Release: Public testing and refinement ahead of the official V3 launch. Turn your PC, Mac, or Linux box into a private AI server.
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.
A TTS model capable of generating ultra-realistic dialogue in one pass.
Deep learning toolkit for text-to-speech, battle-tested in research and production
A complete open-source speech recognition toolkit - ASR, VAD, diarization and serving
Easy-to-use Speech Toolkit including Self-Supervised Learning model, SOTA/Streaming ASR with punctuation, Streaming TTS with text…
Die anderen Projekte der Kategorie Audio mit den meisten Sternen im LibreAI-Katalog — die realistische Auswahl, falls espnet nicht das Richtige ist.
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++
Verwandte Projekte der Kategorie Audio im Katalog, die espnet bei den Sternen am nächsten stehen — zum Weiterstöbern auf beiden Seiten.
A robust, efficient, low-latency speech-to-text library with advanced voice activity detection, wake word activation and instant transcription.
Python library for audio and music analysis
Mozilla's deep-learning text-to-speech library with Tacotron, Glow-TTS and neural vocoders.
EmotiVoice 😊: a Multi-Voice and Prompt-Controlled TTS Engine
Open research toolkit for text-to-speech, voice conversion, singing voice and text-to-audio generation.
VITS — the original end-to-end text-to-speech model: a conditional VAE with adversarial learning, in PyTorch.
Kostenlos und offen — hol dir den Quellcode, gib dem Repository einen Stern und leg los.