Word classification for sign language synthesizer using hidden Markov model
Sign Language Synthesizer is an algorithm developed to provide signing animation from verbal/spoken language. Word classification in Natural Language Processing (NLP) is required to determine grammatically processed sentences for sign language synthesizer. The correct word position of output can pr...
| Main Authors: | , , , |
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| Format: | Proceeding Paper |
| Language: | English English |
| Published: |
IEEE
2014
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/40305/ http://irep.iium.edu.my/40305/1/40305.pdf http://irep.iium.edu.my/40305/3/40305-Word%20classification%20for%20sign%20language%20synthesizer%20using%20hidden%20Markov%20model_SCOPUS.pdf |
| _version_ | 1848781930017849344 |
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| author | Maarif, Haris Al Qodri Akmeliawati, Rini Htike@Muhammad Yusof, Zaw Zaw Gunawan, Teddy Surya |
| author_facet | Maarif, Haris Al Qodri Akmeliawati, Rini Htike@Muhammad Yusof, Zaw Zaw Gunawan, Teddy Surya |
| author_sort | Maarif, Haris Al Qodri |
| building | IIUM Repository |
| collection | Online Access |
| description | Sign Language Synthesizer is an algorithm developed to provide signing animation from verbal/spoken language. Word classification in Natural Language Processing (NLP) is required to determine grammatically processed sentences for sign language synthesizer. The correct word
position of output can provide understanding to users who use sign language synthesizer tools. In this paper, the Hidden Markov Model is proposed and implemented to process the words and locate their corresponding position correctly. The classification was done for Malay language and has resulted in an average accuracy of 74.67 %. |
| first_indexed | 2025-11-14T15:57:23Z |
| format | Proceeding Paper |
| id | iium-40305 |
| institution | International Islamic University Malaysia |
| institution_category | Local University |
| language | English English |
| last_indexed | 2025-11-14T15:57:23Z |
| publishDate | 2014 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | iium-403052017-08-24T07:30:44Z http://irep.iium.edu.my/40305/ Word classification for sign language synthesizer using hidden Markov model Maarif, Haris Al Qodri Akmeliawati, Rini Htike@Muhammad Yusof, Zaw Zaw Gunawan, Teddy Surya TK Electrical engineering. Electronics Nuclear engineering Sign Language Synthesizer is an algorithm developed to provide signing animation from verbal/spoken language. Word classification in Natural Language Processing (NLP) is required to determine grammatically processed sentences for sign language synthesizer. The correct word position of output can provide understanding to users who use sign language synthesizer tools. In this paper, the Hidden Markov Model is proposed and implemented to process the words and locate their corresponding position correctly. The classification was done for Malay language and has resulted in an average accuracy of 74.67 %. IEEE 2014-11-25 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/40305/1/40305.pdf application/pdf en http://irep.iium.edu.my/40305/3/40305-Word%20classification%20for%20sign%20language%20synthesizer%20using%20hidden%20Markov%20model_SCOPUS.pdf Maarif, Haris Al Qodri and Akmeliawati, Rini and Htike@Muhammad Yusof, Zaw Zaw and Gunawan, Teddy Surya (2014) Word classification for sign language synthesizer using hidden Markov model. In: 5th International Conference on Information & Communication Technology for The Muslim World (ICT4M 2014), 17th--19th November 2014, Kuching, Sarawak. http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7020617 10.1109/ICT4M.2014.7020617 |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Maarif, Haris Al Qodri Akmeliawati, Rini Htike@Muhammad Yusof, Zaw Zaw Gunawan, Teddy Surya Word classification for sign language synthesizer using hidden Markov model |
| title | Word classification for sign language synthesizer using hidden Markov model |
| title_full | Word classification for sign language synthesizer using hidden Markov model |
| title_fullStr | Word classification for sign language synthesizer using hidden Markov model |
| title_full_unstemmed | Word classification for sign language synthesizer using hidden Markov model |
| title_short | Word classification for sign language synthesizer using hidden Markov model |
| title_sort | word classification for sign language synthesizer using hidden markov model |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://irep.iium.edu.my/40305/ http://irep.iium.edu.my/40305/ http://irep.iium.edu.my/40305/ http://irep.iium.edu.my/40305/1/40305.pdf http://irep.iium.edu.my/40305/3/40305-Word%20classification%20for%20sign%20language%20synthesizer%20using%20hidden%20Markov%20model_SCOPUS.pdf |