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Your search keyword '"automatic sign language translator"' showing total 2 results
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2 results on '"automatic sign language translator"'

1. VirtualSign: Revolutionizing Accessibility and Inclusivity in Education Through Automatic Sign Language Translation

Author

Escudeiro, Paula, Gouveia, Márcia Campos, Escudeiro, Francisca, Escudeiro, Nuno, Kacprzyk, Janusz, Series Editor, Gomide, Fernando, Advisory Editor, Kaynak, Okyay, Advisory Editor, Liu, Derong, Advisory Editor, Pedrycz, Witold, Advisory Editor, Polycarpou, Marios M., Advisory Editor, Rudas, Imre J., Advisory Editor, Wang, Jun, Advisory Editor, Yang, Xin-She, editor, Sherratt, R. Simon, editor, Dey, Nilanjan, editor, and Joshi, Amit, editor

Published
2025
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2. Assistive technology for relieving communication lumber between hearing/speech impaired and hearing people

Author

Rini Akmeliawati, Donald Bailey, Sara Bilal, Serge Demidenko, Nuwan Gamage, Shujjat Khan, Ye Chow Kuang, Melanie Ooi, and Gourab Sen Gupta

Subjects
sign language recognition, hearing, handicapped aids, assisted living, language translation, feature extraction, hidden Markov models, Linux, virtual machines, assistive technology, hearing impaired people, speech impaired people, automatic sign language translator, speech impaired communities, hearing impaired communities, system architecture, feature recognition, static signs, dynamic signs, hidden Markov model, segmentation signature, Windows7 operating systems, LINUX Fedora 16 operating systems, VMware workstation, Malaysian sign language, Engineering (General). Civil engineering (General), TA1-2040
Abstract

This study proposes an automatic sign language translator, which is developed as assistive technology to help the hearing/speech impaired communities to communicate with the rest of the world. The system architecture, which includes feature extraction and recognition stages is described in detail. The signs are classified into two types: static and dynamic. Various types of sign features are presented and analysed. Recognition stage considers the hidden Markov model and segmentation signature. Real-time implementation of the system with the use of Windows7 and LINUX Fedora 16 operating systems with VMware workstation is presented in detail. The system has been successfully tested on Malaysian sign language.

Published
2014
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