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This paper addresses the challenges in Sign Language Recognition Systems (SLR) and Sign Language Translation (SLT), focusing on the translation of sign language to text/speech and the reverse process. The unique grammatical structures of sign languages pose a core problem, prompting the development of computational models. The Sign Language Translation (SLT) module, translating recognized gloss into spoken language text, presents a formidable challenge due to grammatical and semantic intricacies. Additionally, the need for diverse datasets, including various sign language dialects in India, further complicates the development of robust SLR and SLT systems. The paper explores technological advancements, challenges, and solutions in both modules, contributing to inclusive communication tools.
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Sindhu et al. (2024) studied this question.
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