English(EN) SimulSense: Sense-Driven Interpreting for Efficient Simultaneous Speech Translation

新的SimulSense框架提高了同声传译效率

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-27 04:00

研究人员开发了SimulSense，一个用于同声传译（SimulST）的新框架，旨在模仿人类译员。与目前将SimulST视为对话任务并依赖计算成本高昂的LLM推理的系统不同，SimulSense持续处理输入语音，并基于感知的“意义单元”做出翻译决策。据报道，这种方法带来了更好的质量-延迟权衡和显著提高的实时效率，决策速度比现有方法快9.6倍。 AI

影响这项研究可能带来更高效、更像人类的同声传译系统，从而改善实时通信工具。

排序理由该集群描述了在arXiv上的学术论文中提出的一个新颖框架。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

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Newsworthiness bucket: Tool; 该集群描述了在arXiv上的学术论文中提出的一个新颖框架。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

arXiv cs.CL TIER_1 English(EN) · Haotian Tan, Hiroki Ouchi, Sakriani Sakti · 2026-10-27 04:00

SimulSense：驱动感知的高效同声传译语音翻译

arXiv:2509.21932v3 Announce Type: replace Abstract: How to make human-interpreter-like read/write decisions for simultaneous speech translation (SimulST) systems? Current state-of-the-art systems formulate SimulST as a multi-turn dialogue task, requiring specialized interleaved t…

本文如何被排名

报道来源 [1]

SimulSense：驱动感知的高效同声传译语音翻译

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