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Adaptive language processing unit for Malaysian sign language synthesizer

Maarif, Haris Al Qodri and Gunawan, Teddy Surya and Akmeliawati, Rini (2021) Adaptive language processing unit for Malaysian sign language synthesizer. IAES International Journal of Robotics and Automation (IJRA), 10 (4). pp. 326-339. ISSN 2089-4856 E-ISSN 2722-2586

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Language Processing Unit (LPU) is a system built to process text-based data to comply with the rules of sign language grammar. This system was developed as an important part of the sign language synthesizer system. Sign language (SL) uses different grammatical rules from the spoken/verbal language, which only involves the important words that Hearing/Impaired Speech people can understand. Therefore, it needs word classification by LPU to determine grammatically processed sentences for the sign language synthesizer. However, the existing language processing unit in SL synthesizers suffers time lagging and complexity problems, resulting in high processing time. The two features, i.e., the computational time and success rate, become trade-offs which means the processing time becomes longer to achieve a higher success rate. This paper proposes an adaptive Language Processing Unit (LPU) that allows processing the words from spoken words to Malaysian SL grammatical rule that results in relatively fast processing time and a good success rate. It involves n-grams, NLP, and Hidden Markov Models (HMM)/Bayesian Networks as the classifier to process the text-based input. As a result, the proposed LPU system has successfully provided an efficient (fast) processing time and a good success rate compared to LPU with other edit distances (Mahalanobis, Levensthein, and Soundex). The system has been tested on 130 text-input sentences with several words ranging from 3 to 10 words. Results showed that the proposed LPU could achieve around 1.497ms processing time with an average success rate of 84.23% for a maximum of ten-word sentences.

Item Type: Article (Journal)
Additional Information: 5588/94301
Uncontrolled Keywords: Classifier, distance algorithm, Malaysian sign language, Natural language prrocessing
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK7800 Electronics. Computer engineering. Computer hardware. Photoelectronic devices
Kulliyyahs/Centres/Divisions/Institutes (Can select more than one option. Press CONTROL button): Kulliyyah of Engineering > Department of Electrical and Computer Engineering
Kulliyyah of Engineering
Depositing User: Prof. Dr. Teddy Surya Gunawan
Date Deposited: 02 Dec 2021 12:18
Last Modified: 02 Dec 2021 12:18
URI: http://irep.iium.edu.my/id/eprint/94301

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