Studying Data Analysis on the Need of Sign Language Recognition Technology for Deaf & Mute Students
Keywords:
Sign Language Recognition System, Data analysis on differently abled students, Statistical analysis of speech and hearing-impaired students, Sign language in Oman, Arabic Sign LanguageAbstract
Since there are more than 300 different sign languages in the globe, it can be difficult for persons who have hearing or speech disabilities to communicate successfully. 34% of disabled Omani persons have hearing impairments (Oman Observer, 2021). An interesting and crucial field of research is the use of sign language recognition software to assist students with speech and auditory impairments in academic settings and the workforce. The goal of the study is to examine the demand for sign language recognition technology among students who have speech and auditory impairments by giving a thorough analysis of the communication hurdles that a Sign Language Recognition System (SLR) can eliminate. With an emphasis on Arabic Sign Language (ArSL), it offers a methodical comparison of various existing SLR systems. A more thorough grasp of the research issue is provided through the use of a mixed-methods technique that combines surveys and interviews. The study's conclusions point to a pressing need for sign language recognition technology in both education and employment for children with speech and hearing impairments. The results of the study have significant ramifications for the creation and application of sign language recognition software in academic and professional settings. There is certainly room for more investigation into the applications of sign language recognition technologies. In order to promote the employability of deaf and dumb persons in Oman, the study is anticipated to contribute to the development of essential frameworks and standards.
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