Development of gender and race recognition system using speech and recognition by using frequency spectrum

In this thesis, the development of an algorithm and system that is able to recognize gender and races by using the speech frequency spectrum is presented. Some of the features extracted are the formant frequency and fundamental frequency of speech signals. The formant frequencies are obtained by fi...

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Main Author: Ng Siew Fong
Other Authors: Sazali Yaakob, Prof. Dr. (Advisor)
Format: Learning Object
Language:English
Published: School of Mechatronics Engineering 2009
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Online Access:http://dspace.unimap.edu.my/xmlui/handle/123456789/4600
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spelling my.unimap-46002009-02-05T04:44:16Z Development of gender and race recognition system using speech and recognition by using frequency spectrum Ng Siew Fong Sazali Yaakob, Prof. Dr. (Advisor) Recognition system -- Design and construction Speech recognition Speech processing systems Automatic speech recognition Speech perception Linear prediction coefficient In this thesis, the development of an algorithm and system that is able to recognize gender and races by using the speech frequency spectrum is presented. Some of the features extracted are the formant frequency and fundamental frequency of speech signals. The formant frequencies are obtained by finding a set of predictor coefficient that minimizes the mean square error over a short segment of speech waveform. Whereas the fundamental frequency is estimated by finding a peak in the auto-correlation function with a corresponding delay. Results obtained using this approach to identify the gender by using formant frequency and fundamental frequency has proven to be practically applicable. The Back-Propagation Neural Network has been chosen for the classification purposes. These features will be fed into the neural network for training until it is able to outputs the appropriate gender and races. The speech recognition application is implemented using the Digital Signal Processor (DSP). The well trained network parameters were applied in the DSP by the new architecture support features that facilitate the development of efficient high level languages. Hence, C code was chosen to read a set of input features, as the weights are being adjusted and weights sum output from input features, the corresponding results are finally displayed on the Liquid Crystal Display (LCD) through DSP. 2009-02-05T04:44:15Z 2009-02-05T04:44:15Z 2008-05 Learning Object http://hdl.handle.net/123456789/4600 en School of Mechatronics Engineering
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 Recognition system -- Design and construction
Speech recognition
Speech processing systems
Automatic speech recognition
Speech perception
Linear prediction coefficient
spellingShingle Recognition system -- Design and construction
Speech recognition
Speech processing systems
Automatic speech recognition
Speech perception
Linear prediction coefficient
Ng Siew Fong
Development of gender and race recognition system using speech and recognition by using frequency spectrum
description In this thesis, the development of an algorithm and system that is able to recognize gender and races by using the speech frequency spectrum is presented. Some of the features extracted are the formant frequency and fundamental frequency of speech signals. The formant frequencies are obtained by finding a set of predictor coefficient that minimizes the mean square error over a short segment of speech waveform. Whereas the fundamental frequency is estimated by finding a peak in the auto-correlation function with a corresponding delay. Results obtained using this approach to identify the gender by using formant frequency and fundamental frequency has proven to be practically applicable. The Back-Propagation Neural Network has been chosen for the classification purposes. These features will be fed into the neural network for training until it is able to outputs the appropriate gender and races. The speech recognition application is implemented using the Digital Signal Processor (DSP). The well trained network parameters were applied in the DSP by the new architecture support features that facilitate the development of efficient high level languages. Hence, C code was chosen to read a set of input features, as the weights are being adjusted and weights sum output from input features, the corresponding results are finally displayed on the Liquid Crystal Display (LCD) through DSP.
author2 Sazali Yaakob, Prof. Dr. (Advisor)
author_facet Sazali Yaakob, Prof. Dr. (Advisor)
Ng Siew Fong
format Learning Object
author Ng Siew Fong
author_sort Ng Siew Fong
title Development of gender and race recognition system using speech and recognition by using frequency spectrum
title_short Development of gender and race recognition system using speech and recognition by using frequency spectrum
title_full Development of gender and race recognition system using speech and recognition by using frequency spectrum
title_fullStr Development of gender and race recognition system using speech and recognition by using frequency spectrum
title_full_unstemmed Development of gender and race recognition system using speech and recognition by using frequency spectrum
title_sort development of gender and race recognition system using speech and recognition by using frequency spectrum
publisher School of Mechatronics Engineering
publishDate 2009
url http://dspace.unimap.edu.my/xmlui/handle/123456789/4600
_version_ 1643787963435319296
score 13.211869