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arXiv · 2406.10223

Diffusion Synthesizer for Efficient Multilingual Speech to Speech Translation

Nameer Hirschkind·Xiao Yu·Mahesh Kumar Nandwana·Joseph Liu·Eloi DuBois·Dao Le·Nicolas Thiebaut·Colin Sinclair·Kyle Spence·Charles Shang·Zoe Abrams·Morgan McGuire
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Abstract

We introduce DiffuseST, a low-latency, direct speech-to-speech translation system capable of preserving the input speaker's voice zero-shot while translating from multiple source languages into English. We experiment with the synthesizer component of the architecture, comparing a Tacotron-based synthesizer to a novel diffusion-based synthesizer. We find the diffusion-based synthesizer to improve MOS and PESQ audio quality metrics by 23\% each and speaker similarity by 5\% while maintaining comparable BLEU scores. Despite having more than double the parameter count, the diffusion synthesizer has lower latency, allowing the entire model to run more than 5$\times$ faster than real-time.

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Nameer Hirschkind, Xiao Yu, Mahesh Kumar Nandwana, Joseph Liu, Eloi DuBois, Dao Le, Nicolas Thiebaut, Colin Sinclair, Kyle Spence, Charles Shang, Zoe Abrams, Morgan McGuire. 2024-06-14. Diffusion Synthesizer for Efficient Multilingual Speech to Speech Translation. https://arxiv.org/abs/2406.10223

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