新型多模态LLM在无词汇手语翻译方面达到最先进水平

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-07 04:00

研究人员开发了ViPo-MLLM，一个新颖的多模态大型语言模型，用于无词汇手语翻译。该框架整合了时空RGB数据和人体姿态特征，采用专用的编码器处理模态内动力学，并利用跨模态注意力处理长距离依赖。ViPo-MLLM在PHOENIX14T和CSL-Daily数据集上取得了新的最先进成果，展示了与基于词汇的方法相比具有竞争力的性能。 AI

影响推动了无词汇手语翻译的进步，可能提高聋哑和听力障碍社群的可及性。

排序理由详细介绍新模型和基准结果的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Ahmed Abul Hasanaath, Bicheng Xu, Mir Rayat Imtiaz Hossain, Leonid Sigal, Hamzah Luqman · 2026-07-07 04:00

ViPo-MLLM：用于无词汇手语翻译的视觉姿态多模态大语言模型

arXiv:2607.03657v1 Announce Type: cross Abstract: Gloss-free Sign Language Translation (SLT) translates sign language videos into spoken-language sentences without gloss annotations, avoiding costly labeling but requiring fine-grained modeling of hands, body, and facial cues. Exi…

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ViPo-MLLM：用于无词汇手语翻译的视觉姿态多模态大语言模型

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