SIBI (Sistem Isyarat Bahasa Indonesia) translation using Convolutional Neural Network (CNN)

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A.R. Syulistyo, D.S. Hormansyah, P.Y. Saputra

2020 IOP Conference Series: Materials Science and Engineering Vol. 732 Issue 1 Conference paper Cited by 4 SDG 4 Quartile

Abstract

Deaf people are one of those with disabilities who cannot speak and hear. Deaf people using sign language for communication who use sign language with hand gestures, body and convey facial expressions using sign language. One important component in sign language is the alphabetical finger or the manual alphabet needed to complete communication. The alphabet of the finger is done by spelling words on spoken language, by spelling letter by letter using a finger. This method is used to spell the name or mention the word. However, not everyone understands sign language, so tools needed to bridge communication between people who are deaf with normal people. One solution that will be offered is to use computer technology as a tool to recognize sign language. The technology is an automatic language translator system that process input images using by using the Convolutional Neural Network (CNN). On this research consist of 3 class such us A, assalamualaikum and hallo which get the accuracy respectively 100% for each class. © Published under licence by IOP Publishing Ltd.

Affiliations

State Polytechnic of Malang, Malang, Indonesia

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