Malaysian vowel recognition based on spectral envelope using bandwidth approach

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Main Authors:	Fadzilah, Siraj, Shahrul Azmi, M. Y., Paulraj, Murugesapandian, Sazali, Yaacob
Other Authors:	fad173@uum.edu.my
Format:	Working Paper
Language:	English
Published:	Institute of Electrical and Electronics Engineering (IEEE) 2009
Subjects:	Bandwidth approach Logistic regression Neural network Spectral envelope Vowel recognition Backpropagation Speech recognition Regression analysis
Online Access:	http://dspace.unimap.edu.my/xmlui/handle/123456789/7399
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Institution:	Universiti Malaysia Perlis
Language:	English

id	my.unimap-7399
record_format	dspace
spelling	my.unimap-73992009-12-10T06:21:46Z Malaysian vowel recognition based on spectral envelope using bandwidth approach Fadzilah, Siraj Shahrul Azmi, M. Y. Paulraj, Murugesapandian Sazali, Yaacob fad173@uum.edu.my Bandwidth approach Logistic regression Neural network Spectral envelope Vowel recognition Backpropagation Speech recognition Regression analysis Link to publisher's homepage at http://ieeexplore.ieee.org 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. In this paper, a new feature extraction method is presented to identify vowels recorded from 80 Malaysian speakers. The features are obtained from Vocal Tract Model based on Bandwidth (BW) approach. The bandwidth is determined by finding the frequency where the spectral energy is 3dB below the peak. Average gain was calculated from these bandwidths. Classification results from Bandwidth Approach were then compared with results from 14 MFCC Coefficients using BPNN (Backpropagation Neural Network), MLR (Multinomial Logistic Regression) and LDA (Linear Discriminative Analysis). Classification accuracy obtained shows Bandwidth Approach performs better than MFCC using all these classifiers. 2009-12-10T06:21:46Z 2009-12-10T06:21:46Z 2009-05-25 Working Paper p.363-368 978-1-4244-4154-9 http://ieeexplore.ieee.org/search/wrapper.jsp?arnumber=5072013 http://hdl.handle.net/123456789/7399 en Proceedings of the 3rd Asia International Conference on Modelling and Simulation (AMS 2009) Institute of Electrical and Electronics Engineering (IEEE)
institution	Universiti Malaysia Perlis
building	UniMAP Library
collection	Institutional Repository
continent	Asia
country	Malaysia
content_provider	Universiti Malaysia Perlis
content_source	UniMAP Library Digital Repository
url_provider	http://dspace.unimap.edu.my/
language	English
topic	Bandwidth approach Logistic regression Neural network Spectral envelope Vowel recognition Backpropagation Speech recognition Regression analysis
spellingShingle	Bandwidth approach Logistic regression Neural network Spectral envelope Vowel recognition Backpropagation Speech recognition Regression analysis Fadzilah, Siraj Shahrul Azmi, M. Y. Paulraj, Murugesapandian Sazali, Yaacob Malaysian vowel recognition based on spectral envelope using bandwidth approach
description	Link to publisher's homepage at http://ieeexplore.ieee.org
author2	fad173@uum.edu.my
author_facet	fad173@uum.edu.my Fadzilah, Siraj Shahrul Azmi, M. Y. Paulraj, Murugesapandian Sazali, Yaacob
format	Working Paper
author	Fadzilah, Siraj Shahrul Azmi, M. Y. Paulraj, Murugesapandian Sazali, Yaacob
author_sort	Fadzilah, Siraj
title	Malaysian vowel recognition based on spectral envelope using bandwidth approach
title_short	Malaysian vowel recognition based on spectral envelope using bandwidth approach
title_full	Malaysian vowel recognition based on spectral envelope using bandwidth approach
title_fullStr	Malaysian vowel recognition based on spectral envelope using bandwidth approach
title_full_unstemmed	Malaysian vowel recognition based on spectral envelope using bandwidth approach
title_sort	malaysian vowel recognition based on spectral envelope using bandwidth approach
publisher	Institute of Electrical and Electronics Engineering (IEEE)
publishDate	2009
url	http://dspace.unimap.edu.my/xmlui/handle/123456789/7399
_version_	1643788790815260672

Malaysian vowel recognition based on spectral envelope using bandwidth approach

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