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Please use this identifier to cite or link to this item: http://dspace.unimap.edu.my:80/xmlui/handle/123456789/7399

Title: Malaysian vowel recognition based on spectral envelope using bandwidth approach
Authors: Fadzilah, Siraj
Shahrul Azmi, M. Y.
Paulraj, Murugesapandian
Sazali, Yaacob
???metadata.dc.contributor.url???: fad173@uum.edu.my
Keywords: Bandwidth approach;Logistic regression;Neural network;Spectral envelope;Vowel recognition;Backpropagation;Speech recognition;Regression analysis
Issue Date: 25-May-2009
Publisher: Institute of Electrical and Electronics Engineering (IEEE)
Citation: p.363-368
Series/Report no.: Proceedings of the 3rd Asia International Conference on Modelling and Simulation (AMS 2009)
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. 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.
Description: Link to publisher's homepage at http://ieeexplore.ieee.org
URI: http://ieeexplore.ieee.org/search/wrapper.jsp?arnumber=5072013
ISBN: 978-1-4244-4154-9
Appears in Collections:Paulraj Murugesa Pandiyan, Prof. Dr.
Conference Papers
Sazali Yaacob, Prof. Dr.

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