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New method enables latency control for simultaneous speech translation

By PulseAugur Editorial · [1 sources] ·

Researchers have developed DIAL-S2ST, a novel post-training method designed to control inference-time latency in simultaneous speech-to-speech translation models. This approach leverages self-distillation from lookahead predictions to enable earlier speech emissions without requiring paired target data. By training a single LoRA adapter, the system allows for adjustable timing at inference, demonstrating effective adaptation with just 10 hours of source speech for French-to-English translation. AI

IMPACT This method could improve the real-time performance and user experience of speech translation systems.

RANK_REASON The cluster contains a research paper detailing a new method for speech translation. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New method enables latency control for simultaneous speech translation

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The cluster contains a research paper detailing a new method for speech translation. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Jeongsoo Choi, Junseok Ahn, Joon Son Chung ·

    DIAL-S2ST: Learning Latency Control for Simultaneous Speech-to-Speech Translation

    arXiv:2610.32214v1 Announce Type: new Abstract: We propose DIAL-S2ST, a post-training method for learning inference-time latency control in simultaneous speech-to-speech translation models. Our approach reuses pretrained translation capabilities through self-distillation from loo…

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