Abstract
Sign Language (SL), also known as gesture-based language, is used by people with hearing loss to convey their messages. SL interpreters are required for people who do not have the knowledge of SL, but interpreters are not readily available. Thus, a machine-based translation system is required to translate the text into SL. In this article, a system is implemented for translating English text into Indian Sign Language (ISL). It acts as a tool for human-computer interaction and eliminates the need for an ISL human interpreter for communicating with people who have hearing loss. The system features a rich corpus of English words and commonly used sentences. It consists of components such as an ISL parser, the Hamburg Notation System, the Signing Gesture Mark-up Language, and 3D avatar animation for generating SL according to ISL grammar. The proposed system has been tested rigorously by SL users. The results proved that the proposed system is highly efficient and achieves an average score of accuracy (i.e., 4.2 for English words and 3.8 for sentences on a scale from 1 to 5). The performance of proposed system has also been evaluated using the BiLingual Evaluation Understudy score, which results in 0.95 accuracy. The proposed system and mobile application together has the potential to bring individuals with hearing loss and their entourage together.
- Tirthankar Dasgupta, Sandipan Dandpat, and Anupam Basu. 2008. Prototype machine translation system from text-to-Indian sign language. In Proceedings of the IJCNLP-08 Workshop on NLP for Less Privileged Languages.Google Scholar
Digital Library
- Purushottam Kar, Madhusudan Reddy, A. Mukherjee, and Achla M. Raina. 2007. INGIT: Limited domain formulaic translation from Hindi strings to Indian sign language. ICON 52 (2007), 53--54.Google Scholar
- Thomas Hanke. 2004. HamNoSys—Representing sign language data in language resources and language processing contexts. In Proceedings of the 4th International Conference on Language Resources and Evaluation (LREC’04), Vol. 4. 1--6.Google Scholar
- Tony Veale and Alan Conway. 1994. Cross modal comprehension in ZARDOZ an English to sign-language translation system. In Proceedings of the 7th International Workshop on Natural Language Generation. 249--252.Google Scholar
Digital Library
- Liwei Zhao, Karin Kipper, William Schuler, Christian Vogler, Norman Badler, and Martha Palmer. 2000. A machine translation system from English to American Sign Language. In Proceedings of the Conference of the Association for Machine Translation in the Americas. 54--67.Google Scholar
Cross Ref
- Stuart M. Shieber. 1994. Restricting the weak-generative capacity of synchronous tree-adjoining grammars. Computational Intelligence 10, 4 (1994), 371--385. DOI:https://doi.org/10.1111/j.1467-8640.1994.tb00003.xGoogle Scholar
Cross Ref
- Norman I. Badler, Martha S. Palmer, and Rama Bindiganavale. 1999. Animation control for real-time virtual humans. Communications of the ACM 42, 8 (1999), 64--73.Google Scholar
Digital Library
- Sami M. Halawani and A. B. Zaitun. 2012. An avatar based translation system from Arabic speech to Arabic sign language for deaf people. International Journal of Information Science and Education 2 (2012), 13--20.Google Scholar
- Syed Faraz Ali, Gouri Sankar Mishra, and Ashok Kumar Sahoo. 2013. Domain bounded English to Indian sign language translation model. International Journal of Computer Science and Informatics 3, 1 (2013), 41--45.Google Scholar
- Jordi Porta, Fernando Lopez-Colino, Javier Tejedor, and Jose Colas. 2014. A rule-based translation from written Spanish to Spanish sign language glosses. Computer Speech and Language 28, 3 (May 2014), 788--811. DOI:https://doi.org/10.1016/j.csl.2013.10.003Google Scholar
Digital Library
- Jagriti Mishra, Gouri Sankar Mishra, Kiran Ravulakollu, Ravi Rastogi, and K. M. Rafi. 2014. Machine translation of Indian signs for endocrinologist. International Journal of Emerging Technology and Advanced Engineering 4, 4 (2014), 112--116.Google Scholar
- Rupinder Kaur and Parteek Kumar. 2014. HamNoSys generation system for sign language. In Proceedings of the International Conference on Advances in Computing, Communications, and Informatics (ICACCI’14). IEEE, Los Alamitos, CA, 2727--2734.Google Scholar
Cross Ref
- Jestin Joy and Kannan Balakrishnan. 2014. A prototype Malayalam to sign language automatic translator. arXiv:1412.7415.Google Scholar
- Sandeep Kaur and Maninder Singh. 2015. Indian sign language animation generation system. In Proceedings of the 1st International Conference on Next Generation Computing Technologies (NGCT’15). IEEE, Los Alamitos, CA, 909--914.Google Scholar
Cross Ref
- Amit Verma and Sandeep Kaur. 2015. Indian sign language animation generation system for Gurumukhi script. International Journal of Computer Science and Technology 6, 3 (July 2015), 117–121.Google Scholar
- Paras Vij and Parteek Bhatia. 2016. Translator of Hindi Text to ISL and Extension of ISL Dictionary with WordNet. Master’s Thesis. Thapar University.Google Scholar
- Lalit Goyal and Vishal Goyal. 2016. Development of Indian sign language dictionary using synthetic animations. Indian Journal of Science and Technology 9, 32 (Aug. 2016), 1--5. DOI:https://doi.org/10.17485/ijst/2016/v9i32/100729Google Scholar
Cross Ref
- Ulrike Zeshan. 2000. Sign Language in Indo-Pakistan: A Description of a Signed Language. John Benjamins Publishing Company. DOI:https://doi.org/10.1075/z.101Google Scholar
- Samar Sinha. 2017. Indian Sign Language: A Linguistic Analysis of Its Grammar. Gallaudet University Press. https://www.amazon.com/Indian-Sign-Language-Linguistic-Analysis/dp/1944838082Google Scholar
- Enoch O. Aboh, Roland Pfau, and Ulrike Zeshan. 2005. When a Wh-word is not a Wh-word: The case of Indian sign language. In The Yearbook of South Asian Languages and Linguistics, R. Singh (Ed.). Amsterdam Center for Language and Communication, Amsterdam, the Netherlands, 11–43. DOI:https://doi.org/10.1515/9783110186185.11Google Scholar
- Sugandhi, Parteek Kumar, and Sanmeet Kaur. 2018. Online multilingual dictionary using Hamburg notation for avatar-based Indian sign language generation system. International Journal of Cognitive and Language Sciences 12, 8 (2018), 120–127.Google Scholar
- Ralph Elliott, Javier Bueno, Richard Kennaway, and John Glauert. 2010. Towards the integration of synthetic SL animation with avatars into corpus annotation tools. In Proceedings of the 4th Workshop on the Representation and Processing of Sign Languages: Corpora and Sign Language Technologies. 84--87.Google Scholar
- Daniel Stein, Jan Bungeroth, and Hermann Ney. 2006. Morpho-syntax based statistical methods for sign language translation. In Proceedings of the 11th Annual Conference of the European Association for Machine Translation. 169--177.Google Scholar
Index Terms
Sign Language Generation System Based on Indian Sign Language Grammar
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