Sign Language A-Z Alphabet Introduction American Sign Language using Support Vector Machine

Muhammad Rasuandi, Muhammad Fachrurrozi, Anggina primanita

Abstract

Deafness is a condition where a person's hearing cannot function
normally. As a result, these conditions affect ongoing interactions,
making it difficult to understand and convey information.
Communication problems for the deaf are handled through the
introduction of various forms of sign language, one of which is
American Sign Language. Computer Vision-based sign language
recognition often takes a long time to develop, is less accurate, and
cannot be done directly or in real-time. As a result, a solution is
needed to overcome this problem. In the system training process,
using the Support Vector Machine method to classify data and testing
is carried out using the RBF kernel function with C parameters,
namely 10, 50, and 100. The results show that the Support Vector
Machine method with a C parameter value of 100 has better
performance. This is evidenced by the increased accuracy of the RBF
C=100 kernel, which is 99%.

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DOI: https://doi.org/10.36706/sjia.v4i2.74

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