April 2, 2024, 7:48 p.m. | Jia Gong, Lin Geng Foo, Yixuan He, Hossein Rahmani, Jun Liu

cs.CV updates on arXiv.org arxiv.org

arXiv:2404.00925v1 Announce Type: new
Abstract: Sign Language Translation (SLT) is a challenging task that aims to translate sign videos into spoken language. Inspired by the strong translation capabilities of large language models (LLMs) that are trained on extensive multilingual text corpora, we aim to harness off-the-shelf LLMs to handle SLT. In this paper, we regularize the sign videos to embody linguistic characteristics of spoken language, and propose a novel SignLLM framework to transform sign videos into a language-like representation for …

abstract aim arxiv capabilities cs.cl cs.cv good harness language language models language translation large language large language models llms multilingual paper spoken text translate translation type videos

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