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Study on Method of Feature Selection in Speech Content Classification
Digital Object Identifier (DOI) : 10.14569/IJACSA.2014.050412
Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 5 Issue 4, 2014.
Abstract: Information communication is developing rapidly now, Voice communication from a distance is more and more popular. In order to evaluate and classify the content correctly, the acoustic features is used to analyze first in this paper, Orthogonal experiment[1] method is used to find out characteristic of voice that has contribution to the speech content classification then make it and the textual characteristic together. The result of experiments shows that the feature combination of voice and content has better effect on voice content classification, the effectiveness has been improved.
Keywords: acoustic features; orthogonal experiment; the SVM classifier; CHI statistical methods; features level fusion; LBS vector quantization algorithm
Si An and Xinghua Fan, “Study on Method of Feature Selection in Speech Content Classification” International Journal of Advanced Computer Science and Applications(IJACSA), 5(4), 2014. http://dx.doi.org/10.14569/IJACSA.2014.050412
@article{An2014,
title = {Study on Method of Feature Selection in Speech Content Classification},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2014.050412},
url = {http://dx.doi.org/10.14569/IJACSA.2014.050412},
year = {2014},
publisher = {The Science and Information Organization},
volume = {5},
number = {4},
author = {Si An and Xinghua Fan}
}
