CosyVoice is a multilingual text-to-speech system built on large language models that provides complete inference, training, and deployment capabilities. The repository is written in Python and represents the latest iteration in a series of models, with Fun-CosyVoice 3.0 being the current version. The project is actively maintained with a median issue and pull request response latency of 11.4 hours across 1481 tracked items, indicating strong community engagement and developer responsiveness.
The system supports synthesis across 9 major languages including Chinese, English, Japanese, Korean, German, Spanish, French, Italian, and Russian, along with 18 or more Chinese dialects and accents such as Cantonese, Minnan, Sichuan, and Northeastern Chinese. A distinctive feature is its support for zero-shot multilingual and cross-lingual voice cloning, allowing users to generate speech in different languages using reference voice samples without requiring language-specific training data. The model achieves state-of-the-art performance in content consistency, speaker similarity, and prosody naturalness according to evaluation benchmarks presented in the repository.
Fun-CosyVoice 3.0 introduces several advanced capabilities beyond basic text-to-speech. It supports pronunciation inpainting for Chinese Pinyin and English CMU phonemes, providing fine-grained control over pronunciation for production use cases. The system includes text normalization that handles numbers, special symbols, and various text formats without requiring a traditional frontend module. Bi-streaming support enables both text-input streaming and audio-output streaming with latency as low as 150 milliseconds while maintaining high-quality output. The model also responds to various instruction types including language selection, dialect specification, emotional tone, speech speed, and volume adjustments.
The repository demonstrates active development with a clear roadmap spanning from 2024 through 2025. Recent additions include vLLM support for CosyVoice2 and 3, TensorRT-LLM integration for 4x acceleration in deployment scenarios, and Triton TensorRT-LLM runtime support contributed by NVIDIA. The project includes training infrastructure with support for flow matching and reinforcement learning approaches, along with FastAPI server and client implementations for service deployment.
The primary contributor aluminumbox has logged 1192 events in the repository, with additional active contributors JohnHerry and ScottishFold007 contributing 230 and 59 events respectively. The most prevalent issue label is stale with 738 occurrences, reflecting the volume of discussions and feature requests. The repository maintains connections with major open-source projects including Microsoft's VSCode and TypeScript repositories as well as the Rust language repository through overlapping contributors.
CosyVoice is positioned as part of the broader FunAudioLLM ecosystem, which includes complementary projects like FunASR for speech recognition, SenseVoice for emotion detection, and FunClip for AI video processing. The models are available through multiple distribution channels including ModelScope and Hugging Face, with evaluation datasets and papers published for transparency and reproducibility.
