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Speaker Independent Kannada Speech Recognition using Vector quantization

Published on May 2012 by M. A. Anusuya, S. K. Katti
journal_cover_thumbnail

National Conference on Advancement in Electronics & Telecommunication Engineering
Foundation of Computer Science USA
NCAETE - Number 1
May 2012
Authors: M. A. Anusuya, S. K. Katti
38e7eea9-1ec5-4a79-aba7-3e7e9b6b4d5d

M. A. Anusuya, S. K. Katti . Speaker Independent Kannada Speech Recognition using Vector quantization. National Conference on Advancement in Electronics & Telecommunication Engineering. NCAETE, 1 (May 2012), 32-35.

@article{
author = { M. A. Anusuya, S. K. Katti },
title = { Speaker Independent Kannada Speech Recognition using Vector quantization },
journal = { National Conference on Advancement in Electronics & Telecommunication Engineering },
issue_date = { May 2012 },
volume = { NCAETE },
number = { 1 },
month = { May },
year = { 2012 },
issn = 0975-8887,
pages = { 32-35 },
numpages = 4,
url = { /proceedings/ncaete/number1/6593-1083/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Proceeding Article
%1 National Conference on Advancement in Electronics & Telecommunication Engineering
%A M. A. Anusuya
%A S. K. Katti
%T Speaker Independent Kannada Speech Recognition using Vector quantization
%J National Conference on Advancement in Electronics & Telecommunication Engineering
%@ 0975-8887
%V NCAETE
%N 1
%P 32-35
%D 2012
%I International Journal of Computer Applications
Abstract

In this paper a statistical method is used to remove the silence from the speech signal. This method is applied on vector quantization technique to identify the minimum speech patterns that are required while creating the training set of the speech samples. This paper also discusses the importance and efficiency of the algorithms used in vector quantization for the clustering purpose. Also speech recognition accuracies for speaker dependent and speaker independent methods have been evaluated and tabulated in the tables given below. The paper shows the importance of the statistical method analysis of the signal than the normal analysis.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Speech Recognition Isolated Word Uncertainty Vector Quantization Euclidean Distance