The Community for Technology Leaders
2016 International Conference on Frontiers of Information Technology (FIT) (2016)
Islamabad, Pakistan
Dec. 19, 2016 to Dec. 21, 2016
ISBN: 978-1-5090-5300-1
pp: 39-45
Devi Handaya , School of Electrical Engineering and Informatics, Bandung Institute of Technology, Indonesia
Hanif Fakhruroja , School of Electrical Engineering and Informatics, Bandung Institute of Technology, Indonesia
Egi Muhammad Idris Hidayat , School of Electrical Engineering and Informatics, Bandung Institute of Technology, Indonesia
Carmadi Machbub , School of Electrical Engineering and Informatics, Bandung Institute of Technology, Indonesia
ABSTRACT
This paper presents a comparison of two classifier methods based on accuracy level in Indonesian speaker recognition for unclear pronunciation problem in a word, simple sentences, and complete sentences. The first method is Vector Quantization (VQ) based on distortion distance and the second method is Hidden Markov Model (HMM) based on the probability value of the data is observed. Based on the experiments, It can be concluded that HMM method have better accuracy than VQ method especially for pronunciation of simple sentences.
INDEX TERMS
Unclear Pronunciation, Vector Quantization (VQ), Hidden Markov Model (HMM), Indonesian Speaker Recognition
CITATION
Devi Handaya, Hanif Fakhruroja, Egi Muhammad Idris Hidayat, Carmadi Machbub, "Comparison of Indonesian speaker recognition using vector quantization and Hidden Markov Model for unclear pronunciation problem", 2016 International Conference on Frontiers of Information Technology (FIT), vol. 00, no. , pp. 39-45, 2016, doi:10.1109/FIT.2016.7857535
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