VoiceStudioGive every word a voice of its own.

VoiceStudio is an open-source local AI voice workspace for voice cloning, text-to-speech (TTS), transcription, audiobooks and video dubbing. All processing runs on your own computer without uploading data to cloud servers, keeping privacy under your control.

The core software is free and open source under AGPL-3.0. Some bundled models have separate licenses, such as OmniVoice, which is non-commercial. Check each model’s license before use. The software itself has no subscription or credit-based charges.

Downloading and installing the application itself does not require a VPN. However, the GitHub source code and some model weights are hosted overseas, so special network access may be needed when downloading models. Audio generation runs entirely locally and does not require an internet connection.

Yes. Desktop clients are available, along with one-click Docker deployment. You can install and use VoiceStudio on Windows, macOS and Linux.

Yes, in CPU mode, but generation is slower. At least 8 GB of RAM is suggested, with 16 GB or more recommended. NVIDIA CUDA acceleration offers the best results; AMD and Intel graphics generally rely on CPU inference.

A clean, noise-free recording of 5–15 seconds works best. You can try zero-shot cloning with as little as 3 seconds, but stability and similarity will be noticeably lower. Use a single speaker and avoid background music.

Mandarin Chinese is supported, and some engines support a limited number of dialects. VoiceStudio includes multiple TTS engines with theoretical coverage of hundreds of languages. Language capabilities vary greatly, so choose a Chinese-adapted model for Chinese speech.

There are two layers: the software uses AGPL-3.0, while the speech models have their own licenses. The default OmniVoice model is non-commercial. For commercial work, switch to a model with commercial permission and obtain written authorization from the person whose voice you clone.

No. Cloning another person’s voice, including a public figure, without their explicit written authorization carries infringement and legal risks and is not recommended.

WAV, MP3 and FLAC are supported. MP3 supports up to 320 kbps, with sample-rate options of 24 kHz, 44.1 kHz and 48 kHz for short videos, audiobooks and podcasts.

Start with cleaner reference audio, increase generation quality, add suitable punctuation and pauses, try a more expressive TTS engine, and keep the reference audio and generated text in the same language whenever possible.

ElevenLabs is a ready-to-use cloud service with high audio-quality potential and credit-based pricing; audio is uploaded to the cloud. VoiceStudio runs locally and offline, is free without usage quotas, and offers strong privacy, but requires setup and its speed depends on your hardware.

Yes. It includes a long-text segmentation pipeline suited to audiobook production. More RAM is recommended for long texts to avoid out-of-memory interruptions. Subtitle export and dubbing alignment are also supported.

Yes. It provides a local HTTP API that other tools and agents can call after deployment, making it suitable for custom development and automated voiceover workflows.

Check your network first, try a mainland China mirror for model downloads, and verify the Python environment and CUDA version. If memory is insufficient, switch to a lightweight CPU engine. Search the GitHub issue tracker for the specific error.

Yes. You can import a video, extract subtitles, synthesize speech, align the dubbing automatically and export the dubbed video directly. This suits batch dubbing for short videos.

In the normal local version, all reference recordings, voice profiles and generated audio remain on your computer and are not automatically uploaded. If you do not upload or share your voice profiles, third parties cannot obtain your voice data.

Download a ready-made desktop package from Releases rather than compiling from source. Start with a lightweight CPU model to learn the workflow. Prepare about 10 seconds of clean speech for cloning, then gradually move to higher-quality GPU models.