Voxtral TTS
📰 ArXiv cs.AI
Voxtral TTS is a multilingual text-to-speech model that generates natural speech from short reference audio
Action Steps
- Train a speech tokenizer with a hybrid VQ-FSQ quantization scheme
- Adopt a hybrid architecture combining auto-regressive generation and flow-matching for token encoding and decoding
- Use the trained tokenizer to encode and decode semantic and acoustic tokens from reference audio
- Evaluate the generated speech using human evaluation metrics
Who Needs to Know This
AI engineers and researchers working on speech synthesis and natural language processing can benefit from Voxtral TTS, as it enables the generation of high-quality speech from minimal reference audio
Key Insight
💡 Voxtral TTS achieves high-quality speech synthesis with minimal reference audio using a hybrid architecture and novel speech tokenizer
Share This
🗣️ Voxtral TTS generates natural speech from just 3 seconds of reference audio!
Key Takeaways
Voxtral TTS is a multilingual text-to-speech model that generates natural speech from short reference audio
Full Article
Title: Voxtral TTS
Abstract:
arXiv:2603.25551v1 Announce Type: new Abstract: We introduce Voxtral TTS, an expressive multilingual text-to-speech model that generates natural speech from as little as 3 seconds of reference audio. Voxtral TTS adopts a hybrid architecture that combines auto-regressive generation of semantic speech tokens with flow-matching for acoustic tokens. These tokens are encoded and decoded with Voxtral Codec, a speech tokenizer trained from scratch with a hybrid VQ-FSQ quantization scheme. In human eval
Abstract:
arXiv:2603.25551v1 Announce Type: new Abstract: We introduce Voxtral TTS, an expressive multilingual text-to-speech model that generates natural speech from as little as 3 seconds of reference audio. Voxtral TTS adopts a hybrid architecture that combines auto-regressive generation of semantic speech tokens with flow-matching for acoustic tokens. These tokens are encoded and decoded with Voxtral Codec, a speech tokenizer trained from scratch with a hybrid VQ-FSQ quantization scheme. In human eval
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