Lip Motion Pattern Recognition for Indonesian Syllable Pronunciation Utilizing Hidden Markov Model Method
Abstract: A speech therapeutic
tool has been developed to help Indonesian deaf kids learn how to pronounce
words correctly. The applied technique utilized lip movement frames captured by
a camera and inputted them in to a pattern recognition module which can
differentiate between different vowel phonemes pronunciation in Indonesian
language. In this paper, we used one dimensional Hidden Markov Model (HMM)
method for pattern recognition module. The feature used for the training and
test data were composed of six key-points of 20 sequential frames representing
certain phonemes. Seventeen Indonesian phonemes were chosen from the words
usually used by deaf kid special school teachers forspeech therapy. The results
showed that the recognition rates varied on different phonemes articulation, ie.
78% for bilabial/palatal phonemes and 63% for palatal only phonemes. The
condition of the lips also had effect on the result, where female with red lips
has 0.77 correlation coefficient, compare to 0.68 for pale lips and 0.38 for
male with mustaches.
Author: Balza Achmad, Faridah,
Laras Fadillah
Journal Code: jptkomputergg150069
