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Dynamic Sign Language to Text

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dc.contributor.author Ghouse, Omar
dc.date.accessioned 2022-12-20T07:50:55Z
dc.date.available 2022-12-20T07:50:55Z
dc.date.issued 2022
dc.identifier.citation Ghouse, Omar (2022) Dynamic Sign Language to Text. BEng. Dissertation, Informatics Institute of Technology en_US
dc.identifier.issn 2018321
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/1208
dc.description.abstract "Sign language is a medium the hearing and speech impaired use as a communication method to communicate between them and the public. Like normal people use vocal language to communicate the hearing or speech impaired use the sign language to communicate. Sing language also has different languages across the world as to how normal people have different languages. The author of this project takes into consideration of the Sinhala sign language as language medium in this project. The aim of this project is to be able to create a system that can translate the Sinhala sign language into readable text. Which would contribute in closing the gap that the hearing- impaired face when trying to communicate with normal people, as most of them do not understand the sign language. This project focuses on translating dynamic signs into text using neural networks and deep learning algorithms. This project focuses on the use of LSTM neural networks." en_US
dc.language.iso en en_US
dc.subject LSTM neural network en_US
dc.subject Machine learning en_US
dc.subject Dynamic sign language en_US
dc.subject Neural network en_US
dc.title Dynamic Sign Language to Text en_US
dc.type Thesis en_US


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