Paper ID: 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

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.

Submitted: Jun 14, 2024