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All Journal JAREE (Journal on Advanced Research in Electrical Engineering)
Rahman, Muhammad Daffa Abiyyu
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Control & Systems Engineering Electrical & Electronics Engineering

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Facial Movement Recognition Using CNN-BiLSTM in Vowel for Bahasa Indonesia Rahman, Muhammad Daffa Abiyyu; Wicaksono, Alif Aditya; Yuniarno, Eko Mulyanto; Nugroho, Supeno Mardi Susiki
JAREE (Journal on Advanced Research in Electrical Engineering) Vol 8, No 1 (2024): January
Publisher : Department of Electrical Engineering ITS and FORTEI

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/jaree.v8i1.372

Abstract

Speaking is a multimodal phenomenon that has both verbal and non-verbal cues. One of the non-verbal cues in speaking is the facial movement of the subject, which can be used to find the letter being spoken by the subject. Previous research has been done to prove that lip movement can translate to vowels for Bahasa Indonesia, but detecting the whole facial movement is yet to be covered. This research aimed to establish a CNN-BiLSTM model that can learn spoken vowels by reading the subject's facial movements. The CNN-BiLSTM model yielded a 98.66% validation accuracy, with over 94% accuracy for all five vowels. The model is also capable of recognizing whether the subject is currently silent or speaking a vowel with 98.07% accuracy.
Co-Authors Eko Mulyanto Yuniarno Supeno Mardi Susiki Nugroho, Supeno Mardi Wicaksono, Alif Aditya