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Fuzzy Hidden Markov Models for Indonesian Speech Classification

Intan Nurma Yulita^*,** Houw Liong The^**, and Adiwijaya^**

^*Faculty of Informatics, Telkom Institute of Technology 
^**Graduate Faculty, Telkom Institute of Technology, Jalan Telekomunikasi No.1, DayeuhKolot, Jawa Barat 40257, Indonesia

Received: September 15, 2011

Accepted: November 15, 2011

Keywords: fuzzy logic, hidden Markov models, speech, classification, clustering

Journal ref: Journal of Advanced Computational Intelligence and Intelligent Informatics, Vol.16, No.3 pp. 381-387, 2012

Abstract

Indonesia has many tribes, so that there are many dialects. Speech classification is difficult if the database uses speech signals from various people who have different characteristics because of gender and dialect. The different characteristics will influence frequency, intonation, amplitude, and period of the speech. It makes the system must be trained for the various templates reference of speech signal. Therefore, this study has been developed for Indonesian speech classification. The solution is a new combination of fuzzy on hidden Markov models. The result shows a new version of fuzzy hiddenMarkovmodels is better than hidden Markov model. 

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Reference

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