Subspace Approach For Speech Signal Modelling And Classification

Throughout the thesis, the proposed subspace classifiers are assessed on an isolated digit speech recognition problem. For purposes of comparison, the experiments also include two commonly used speech recognizers, i.e., the LPCC and MFCC recognizers.

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Main Author: Tan, Alan Wee Chiat
Format: Thesis
Published: 2007
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id my-mmu-ep.1538
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spelling my-mmu-ep.15382010-10-04T08:23:25Z Subspace Approach For Speech Signal Modelling And Classification 2007-09 Tan, Alan Wee Chiat TK7800-8360 Electronics Throughout the thesis, the proposed subspace classifiers are assessed on an isolated digit speech recognition problem. For purposes of comparison, the experiments also include two commonly used speech recognizers, i.e., the LPCC and MFCC recognizers. 2007-09 Thesis http://shdl.mmu.edu.my/1538/ http://myto.perpun.net.my/metoalogin/logina.php phd doctoral Multimedia University Research Library
institution Multimedia University
collection MMU Institutional Repository
topic TK7800-8360 Electronics
spellingShingle TK7800-8360 Electronics
Tan, Alan Wee Chiat
Subspace Approach For Speech Signal Modelling And Classification
description Throughout the thesis, the proposed subspace classifiers are assessed on an isolated digit speech recognition problem. For purposes of comparison, the experiments also include two commonly used speech recognizers, i.e., the LPCC and MFCC recognizers.
format Thesis
qualification_name Doctor of Philosophy (PhD.)
qualification_level Doctorate
author Tan, Alan Wee Chiat
author_facet Tan, Alan Wee Chiat
author_sort Tan, Alan Wee Chiat
title Subspace Approach For Speech Signal Modelling And Classification
title_short Subspace Approach For Speech Signal Modelling And Classification
title_full Subspace Approach For Speech Signal Modelling And Classification
title_fullStr Subspace Approach For Speech Signal Modelling And Classification
title_full_unstemmed Subspace Approach For Speech Signal Modelling And Classification
title_sort subspace approach for speech signal modelling and classification
granting_institution Multimedia University
granting_department Research Library
publishDate 2007
_version_ 1747829396073349120