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Classification of Malaysian vowels using formant based features


Mohd Yusof, S. A. and M., Paulraj and Yaacob, S. (2008) Classification of Malaysian vowels using formant based features. Journal of ICT, 7. pp. 27-40. ISSN 1675-414X

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Official URL: http://jict.uum.edu.my

Abstract

Automatic speech recognition (ASR) has made great strides with the development of digital signal processing hardware and software, especially using English as the language of choice. Despite of all these advances, machines cannot match the performance of their human counterparts in terms of accuracy and speed, especially in case of speaker independent speech recognition. In this paper, a new feature based on formant is presented and evaluated on Malaysian spoken vowels. These features were classified and used to identify vowels recorded from 80 Malaysian speakers. A back propagation neural network (BPNN) model was developed to classify the vowels. Six formant features were evaluated, which were the first three formant frequencies and the distances between each of them. Results, showed that overall vowel classification rate of these three formant combinations are comparatively the same but differs in terms of individual vowel classification.

Item Type: Article
Uncontrolled Keywords: Speech recognition, vowel detection, format
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: UNSPECIFIED
Depositing User: Mrs. Norazmilah Yaakub
Date Deposited: 01 Sep 2010 01:37
Last Modified: 01 Sep 2010 01:37
URI: http://repo.uum.edu.my/id/eprint/1004

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