新方法增强了富有表现力的语音到语音翻译

作者 PulseAugur 编辑部 · [1 个来源] · 2026-11-05 05:00

研究人员为富有表现力的语音到语音翻译（S2ST）引入了一种新颖的训练数据构建策略。该方法结合了专业配音和多语言语音转换，以创建并行监督，从而在内容、韵律、时间和说话人身份上对源语音和目标语音进行对齐。该策略使用现有的S2ST系统和一种新开发的名为DirectS2ST的端到端方法进行了评估。在英语-德语和英语-西班牙语上的实验表明，所有评估系统在富有表现力的实现方面都有显著改进，其中DirectS2ST显示出最实质性的收益。 AI

影响这项研究可能带来更自然、更富有表现力的语音翻译系统，从而改善跨语言交流。

排序理由该集群包含一篇研究论文，详细介绍了一种新的语音到语音翻译方法。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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报道来源 [1]

arXiv cs.CL TIER_1 English(EN) · Hao Zhang, Ismail Rasim Ulgen, Bismarck Bamfo Odoom, Rui Liu, Zihan Zhang, Berrak Sisman, Philipp Koehn · 2026-11-05 05:00

Holistic Parallel Supervision for Expressive Speech to Speech Translation

arXiv:2611.06010v1 Announce Type: new Abstract: Expressiveness is central to speech-to-speech translation (S2ST), yet existing datasets rarely align source and target speech jointly in content, prosody, timing, and speaker identity. Consequently, current systems often rely on ind…

本文如何被排名

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Holistic Parallel Supervision for Expressive Speech to Speech Translation

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