A SIGN LANGUAGE IDENTIFICATION SYSTEM TO  SUPPORT DISABILITY LANGUAGE USING SUPPORT VECTOR MACHINE

Nguyễn Thanh Nghĩa; Nguyễn Trường Duy; Nguyễn Duy Thảo; Thái Hoàng Linh

doi:10.34238/tnu-jst.11956

A SIGN LANGUAGE IDENTIFICATION SYSTEM TO SUPPORT DISABILITY LANGUAGE USING SUPPORT VECTOR MACHINE

About this article

Received: 03/02/25 Revised: 25/03/25 Published: 26/03/25

Authors

1. Nguyen Thanh Nghia , Ho Chi Minh City University of Technology and Education
2. Nguyen Truong Duy, Ho Chi Minh City University of Technology and Education
3. Nguyen Duy Thao, Ho Chi Minh City University of Technology and Education
4. Thai Hoang Linh, Ho Chi Minh City University of Technology and Education

Abstract

Communication between disability language individuals and non-disabled individuals often faces significant challenges. Currently, there are many people with disability language both worldwide and in Vietnam, and this calls for a useful solution to help individuals with speech impairments communicate more easily. This paper proposes a system to help disability language individuals communicate more easily with non-disabled people. The proposed system included a sensor glove to measure finger movement signals. The measured signals were preprocessed to remove noise and artifacts. The processed signals were then used to identify the letters corresponding to the gestures. Finally, the sounds corresponding to the identification letters were played through a speaker. The system achieves a 99.67% accuracy rate in sign language identification. These promising results suggest that the system could be applied in real-world scenarios to assist individuals with speech disabilities.

Keywords

Sign language identification; Disability language; Support vector machine; Accelerometers sensors; Flex sensors

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DOI: https://doi.org/10.34238/tnu-jst.11956

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