Test Of Vowels In Speech Recognition Using Continuous Density Hidden Markov Model And Development Of Phonetically Balanced-Words In The Filipino Language

Fajardo Arnel C. () and Kim Yoon-joong ()
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Fajardo Arnel C.: Hanbat National University / La Consolacion College Manila
Kim Yoon-joong: Hanbat National University

Balkan Region Conference on Engineering and Business Education, 2014, vol. 1, issue 1, 531-536

Abstract: An Automatic Speech Recognition (ASR) converts the speech signals into words. The recognized words can be the final output or it can be an input for a natural language processing. In this paper, vowel recognizer using Continuous density HMM and Mel-Frequency Cepstral Coefficient (MFCC) were used for feature extraction for its development, and phonetically balanced words (PBW) in Filipino were developed. Thus, this study is a preparation for Filipino Language ASR using HMM. For vowel recognizer, forty speakers were trained (20 male and 20 female speakers). An average accuracy rate of 94.5% was achieved for speaker-dependent test and 90.8% for speaker independent test. For PBW, 2 word lists were developed consisting of 257 words for the 2-syllable Filipino PBW word list and 212 words for the 3-syllable Filipino PBW word list.

Date: 2014
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Persistent link: https://EconPapers.repec.org/RePEc:vrs:brcebe:v:1:y:2014:i:1:p:531-536:n:92

DOI: 10.2478/cplbu-2014-0092

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