Papers with Indian Sign Language

3 papers
OpenHands: Making Sign Language Recognition Accessible with Pose-based Pretrained Models across Languages (2022.acl-long)

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Challenge: a new study examines the performance of pretraining for sign language recognition in low-resource settings.
Approach: They propose using pose extracted through pretrained models as the standard modality of data to reduce training time and enable efficient inference.
Outcome: The proposed model reduces training time and allows efficient inference in sign languages.
iSign: A Benchmark for Indian Sign Language Processing (2024.findings-acl)

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Challenge: Indian Sign Language has limited resources for developing machine learning and data-driven approaches for automated language processing.
Approach: They propose to use a sign language dataset to provide a benchmark for Indian Sign Language processing.
Outcome: The proposed benchmarks will help improve sign language translation models and open up various ways for advancing natural language processing.
CISLR: Corpus for Indian Sign Language Recognition (2022.emnlp-main)

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Challenge: Existing work on natural language processing has shown promising improvements in text classification, translation and generation in widely used spoken languages.
Approach: They propose a new Indian Sign Language corpus for word-level recognition using videos . they propose CISLR model that leverages resource rich American Sign Language to learn generalized features for improving Indian Sign language predictions.
Outcome: The proposed model improves word recognition in Indian Sign Language using video . it leverages resource rich American Sign Language to learn generalized features .

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