两篇新研究论文提出了手语翻译（SLT）的进展。一篇论文详细介绍了一个面向实时句级SLT的硬件感知流式系统，在How2Sign数据集上微调了SHuBERT-ByT5模型，并实现了低延迟。另一篇论文介绍了VTaMo，一个使用显式多粒度对齐来改进无手语词SLT的框架，在多个基准数据集上展示了最先进的性能。 AI
影响 这些进展可以通过实现更自然、实时的交流，显著提高聋哑和听障人士的无障碍性。
排序理由 两篇发表在arXiv上的研究论文，详细介绍了手语翻译的新方法。
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arXiv:2607.11215v1 Announce Type: new Abstract: Most sign language translation (SLT) methods focus on isolated native sign-spoken pairs (e.g., American Sign Language - English). Extending language-specific SLT models to multilingual translation would improve accessibility by enab…
Most sign language translation (SLT) methods focus on isolated native sign-spoken pairs (e.g., American Sign Language - English). Extending language-specific SLT models to multilingual translation would improve accessibility by enabling communication across diverse sign and spoke…
arXiv:2607.09611v1 Announce Type: new Abstract: Most sign language understanding systems operate at the level of isolated signs, limiting their usefulness in natural communication. We study sentence-level sign language translation (SLT) with the primary goal of real-time deployme…
arXiv:2607.09126v1 Announce Type: cross Abstract: Sign language translation (SLT) converts continuous sign videos into spoken language text. Gloss-free approaches leverage pre-trained visual encoders and language models but rely on implicit cross-modal alignment from translation …
Most sign language understanding systems operate at the level of isolated signs, limiting their usefulness in natural communication. We study sentence-level sign language translation (SLT) with the primary goal of real-time deployment rather than proposing a new translation archi…
Sign language translation (SLT) converts continuous sign videos into spoken language text. Gloss-free approaches leverage pre-trained visual encoders and language models but rely on implicit cross-modal alignment from translation supervision alone. We present VTaMo, a framework t…