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Classification of Pattern using Support Vector Machines: An Application for Automatic Speech Recognition

Authors:
Gracieth Batista
Washington Silva
Orlando Filho

Keywords: Support Vector Machines; Classification; Pattern Recognition; Statistical Learning Theory; Application in Speech Recognition.

Abstract:
This paper proposes the implementation of a Support Vector Machine (SVM) for automatic recognition of numerical speech commands. Besides the pre-processing of the speech signal with mel-ceptral coefficients. Also, this paper is used to Discrete Cosine Transform (DCT) to generate a two-dimensional matrix used as input to SVM algorithm for generating the pattern of words to be recognized. The Support Vector Machines represent a new approach to pattern classification. SVM is used to recognize speech patterns from the mean and variance of the speech signal input through the two-dimensional array aforementioned, the algorithm trains and tests those data showing the best response. Finally, the experimental results are presented for the speech recognition applied to Brazilian Portuguese language process.

Pages: 91 to 96

Copyright: Copyright (c) IARIA, 2014

Publication date: August 24, 2014

Published in: conference

ISSN: 2308-4499

ISBN: 978-1-61208-354-4

Location: Rome, Italy

Dates: from August 24, 2014 to August 28, 2014