Introducing Fish-Speech: A Next-Generation Multilingual TTS

Fish-Speech is an advanced multilingual text-to-speech (TTS) system that employs a state-of-the-art transformer-based autoregressive model, integrating large language model reasoning directly into its speech pipeline for improved handling of polyphonic expressions and context-heavy inputs. It features a unique dual-AR architecture with a Slow Transformer for high-level linguistic structure and a Fast Transformer for acoustic detail, which enhances prosody stability and reduces diffusion latency. The Firefly-GAN vocoder, used at the audio layer, achieves nearly full codebook utilization and excels in multilingual and emotional speech synthesis while maintaining high audio quality. Trained on 720,000 hours of audio from diverse language families, Fish-Speech ensures consistent quality across different languages and accents. It demonstrates exceptional performance in word error rate, speaker similarity, and mean opinion score, even surpassing ground-truth transcripts in some aspects. The system is optimized for real-time interaction with a response latency of around 150 milliseconds, making it suitable for AI agents and is available as an open-source project on GitHub.

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