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T5 model scale and motion features boost Indian Sign Language translation

By PulseAugur Editorial · [1 sources] ·

Researchers have investigated the impact of T5 model scale and explicit motion features on translating Indian Sign Language (ISL) to text. Their study compared T5-small, T5-base, and T5-large models, finding that T5-small performed best among spatial-only models in BLEU and ROUGE scores. Augmenting the T5-small model with motion features led to the most significant improvement, achieving the highest BLEU score overall and securing a 5th place ranking in the WSLP 2026 Shared Task. AI

IMPACT Enhances the potential for AI-driven translation of sign languages, improving accessibility for the deaf and hard-of-hearing community.

RANK_REASON The cluster contains an academic paper detailing research into improving a specific AI task (sign language translation) using existing models. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

T5 model scale and motion features boost Indian Sign Language translation

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The cluster contains an academic paper detailing research into improving a specific AI task (sign language translation) using existing models. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Manav Dhamecha, Praveen Kumar Chandaliya, Pruthwik Mishra ·

    Investigating Temporal Motion Features for Pose-to-Text Indian Sign Language Translation

    arXiv:2609.12993v1 Announce Type: cross Abstract: We investigate the effect of pretrained T5 model scale and explicit motion features on pose-to-text Indian Sign Language Translation (SLT) for the WSLP 2026 Shared Task. Pose sequences are projected into the embedding space of T5 …

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