Indian Sign Language Translation using Deep Learning

Likhar, P and Rathna, NG (2021) Indian Sign Language Translation using Deep Learning. In: 9th Edition of IEEE Region 10 Humanitarian Technology Conference, R10-HTC 2021, 30 Sep-2 Oct 2021, Bangalore.

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Abstract

Indian Sign Language is the language used by specially abled population in the Indian subcontinent to communicate with each other. Unfortunately the general population is not aware of the semantics of Indian Sign Language. In this work we present three deep architectures to translate a given video sequence containing the Indian Sign Language sentence to English Language sentence. We have tried to solve this problem using three approaches. First using an LSTM based Sequence to Sequence model(Seq2Seq), second using an LSTM based Seq2Seq model utilising attention, third using an Indian Sign Language Transformer. These models were evaluated on BLEU scores and the transformer model gave a perfect BLEU score of 1.0 on test data. © 2021 IEEE.

Item Type:	Conference Paper
Publication:	IEEE Region 10 Humanitarian Technology Conference, R10-HTC
Publisher:	Institute of Electrical and Electronics Engineers Inc.
Additional Information:	The copyright for this article belongs to Institute of Electrical and Electronics Engineers Inc.
Keywords:	Electric transformer testing; Long short-term memory; Translation (languages), Deep architectures; English languages; General population; Indian sign language transformer; Indian sign languages; Indian subcontinents; Language translation; LSTM; Video sequences, Semantics
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	13 Feb 2022 08:46
Last Modified:	13 Feb 2022 08:46
URI:	http://eprints.iisc.ac.in/id/eprint/71376

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