k2-fsa releases OmniVoice, a zero-shot TTS model claiming 600+ languages
The GitHub project k2-fsa/OmniVoice surfaced on GitHub Trending, describing itself as a massively multilingual zero-shot text-to-speech model covering more than 600 languages. According to its README, it uses a "diffusion language model-style" architecture and supports voice cloning plus voice design via speaker attributes such as gender, age, pitch, accent, dialect and whisper, along with inline tags like [laughter] and pinyin or phoneme pronunciation correction. The project also reports self-measured figures, including an RTF as low as 0.025 (about 40x faster than real time) and FlashInfer speedups over baseline on a single H100; these numbers are vendor-reported and no independent evaluation is cited.
If the 600-plus-language coverage claim holds, the project says it would offer the broadest language coverage among zero-shot TTS models, widening open options for multilingual speech synthesis.
High-Quality Voice Cloning TTS for 600+ Languages
OmniVoice 🌍
OmniVoice is a state-of-the-art massively multilingual zero-shot text-to-speech (TTS) model supporting over 600 languages. Built on a novel diffusion language model-style architecture, it generates high-quality speech with superior inference speed, supporting voice cloning and voice design.
Contents: Key Features | Installation | Quick Start | Python API | Command-Line Tools | Training & Evaluation | Discussion | Citation