Аудио
Whisper
Robust Speech Recognition via Large-Scale Weak Supervision
★ 109,9 тыс. звёздMIT
Смотреть руководство →Piper — проект с открытым исходным кодом из категории «Аудио» от OHF-Voice (OHF-Voice/piper1-gpl на GitHub). У него 5 749 звёзд на GitHub и 553 форка, он распространяется по лицензии GPL-3.0 и последний раз обновлялся на GitHub 28 сентября 2026.
Fast and local neural text-to-speech engine
Speech-to-text, text-to-speech, voice cloning, or music/SFX generation — each project here has a lane.
Python packages, Docker images, and C++ builds cover servers, desktops, and edge devices.
Download the weights or pick a voice; many tools bundle a strong default so you can start immediately.
Transcribe files, synthesize scripts, or generate music — then export standard audio formats.
Open speech recognition now rivals paid APIs on accuracy across languages.
Modern TTS is strikingly human — good enough for narration and voiceovers.
Clone a voice from a short sample for consistent characters and branding.
Compose backing tracks and sound effects from text descriptions.
Entire pipelines work without internet — ideal for private or field use.
Drop-in endpoints that mimic commercial APIs, so existing apps switch easily.
Clone the repository or download the latest release for your OS.
git clone https://github.com/OHF-Voice/piper1-gpl.gitEvery project documents its own setup — the README's install section is the source of truth.
Start the app or server as documented and open the interface it provides.
Excellent — the leading open models match commercial services on clean audio, in many languages.
The tech clones from short samples; only ever clone voices you own or have explicit permission to use.
It is an open-source project at OHF-Voice/piper1-gpl with 553 forks. Check the repo's contributors and recent commits to see how active maintenance is.
Transcription and TTS run on CPU acceptably; GPUs speed up batch jobs and music generation a lot.
Coverage varies — transcription is broadest, TTS quality is best in major languages.
Usually yes, but check both the code license and the model license.
Robust Speech Recognition via Large-Scale Weak Supervision
Port of OpenAI's Whisper model in C/C++
Faster Whisper transcription with CTranslate2
Fast local speech-to-text across 16+ model families, powered by ggml.
Mozilla's deep-learning text-to-speech library with Tacotron, Glow-TTS and neural vocoders.
ToucanTTS: fast, controllable text-to-speech for over 7,000 languages, from Stuttgart's IMS.
Другие проекты из категории «Аудио» с наибольшим числом звёзд в каталоге LibreAI — реалистичный список альтернатив, если Piper вам не подходит.
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++
Соседние проекты из категории «Аудио» в каталоге, ближайшие по числу звёзд к Piper — продолжайте изучать полку по обе стороны от него.
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…
Automatic Speech Recognition with Speaker Diarization based on OpenAI Whisper
Silero Models: pre-trained text-to-speech models made embarrassingly simple
Open-source AI video localization and dubbing for YouTube/Bilibili: speech recognition, subtitle translation, voice cloning, audio mixing and rendering. 开源 A…
Human-level text-to-speech through style diffusion and adversarial training with speech language models.
Turn the beloved Kokoro voice model into an OpenAI-compatible speech API with one Docker command.
Бесплатно и открыто — забирайте исходный код, ставьте звезду репозиторию и начинайте создавать.