VibeVoice is an open-source voice AI framework that combines speech synthesis and speech recognition capabilities. The project provides tools for text-to-speech generation with emotional control and automatic speech recognition that can process long-form audio in a single pass.
The framework addresses the need for unified voice AI by offering both synthesis and recognition in one system. VibeVoice-TTS generates speech with controllable emotional characteristics, while VibeVoice-ASR handles speech-to-text conversion for extended audio, producing structured transcriptions that include speaker identification, timestamps, and content. The ASR component supports over fifty languages and can process up to sixty minutes of audio without segmentation, with optional user-customized context integration.
Developers should consider this tool if they need multilingual speech recognition or emotionally expressive text-to-speech in a single framework. The project suits applications requiring long-form audio processing without manual segmentation, or systems where emotional nuance in synthesized speech matters. The tool integrates with standard machine learning infrastructure, including support for vLLM inference acceleration and compatibility with the Hugging Face Transformers library.
The project maintains active engagement with its user base, with nearly all open issues originating from external adopters rather than the core team, indicating substantial real-world adoption. Maintainers respond to new issues and pull requests within a day. Work in the issue tracker centers on compatibility and bug resolution, reflecting a focus on stability and integration across different deployment environments.
