Beyond Gloss: A Hand-Centric Framework for Gloss-Free Sign Language Translation

• URL: http://arxiv.org/abs/2507.23575v1
• Date: Thu, 31 Jul 2025 14:06:07 GMT
• Title: Beyond Gloss: A Hand-Centric Framework for Gloss-Free Sign Language Translation
• Authors: Sobhan Asasi, Mohamed Ilyas Lakhal, Ozge Mercanoglu Sincan, Richard Bowden,
• Abstract summary: Sign Language Translation (SLT) is a challenging task that requires bridging the modality gap between visual and linguistic information.<n>We introduce textbfBeyondGloss, a novel gloss-free SLT framework that leverages thetemporal-aware reasoning capabilities of VideoLLMs.<n>Beyondtexttext achieves state-of-the-art performance on the PhoenixT14 and CSL-Daily benchmarks, demonstrating the effectiveness of the proposed framework.
• Score: 27.269988311306374
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Sign Language Translation (SLT) is a challenging task that requires bridging the modality gap between visual and linguistic information while capturing subtle variations in hand shapes and movements. To address these challenges, we introduce \textbf{BeyondGloss}, a novel gloss-free SLT framework that leverages the spatio-temporal reasoning capabilities of Video Large Language Models (VideoLLMs). Since existing VideoLLMs struggle to model long videos in detail, we propose a novel approach to generate fine-grained, temporally-aware textual descriptions of hand motion. A contrastive alignment module aligns these descriptions with video features during pre-training, encouraging the model to focus on hand-centric temporal dynamics and distinguish signs more effectively. To further enrich hand-specific representations, we distill fine-grained features from HaMeR. Additionally, we apply a contrastive loss between sign video representations and target language embeddings to reduce the modality gap in pre-training. \textbf{BeyondGloss} achieves state-of-the-art performance on the Phoenix14T and CSL-Daily benchmarks, demonstrating the effectiveness of the proposed framework. We will release the code upon acceptance of the paper.

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