Facebook pixel tracking

The Science and Information (SAI) Organization publishes open-access peer-reviewed journals in computer science and artificial intelligence.

Contact Info
Website thesai.org
Follow Us
Contact Info
Follow Us
Research Article | Open Access |

Study on Method of Feature Selection in Speech Content Classification

Author 1: Si An Author 2: Xinghua Fan
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 5, No. 4 · Published 2014

DOI: 10.14569/IJACSA.2014.050412

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

How to Cite this Article

An, S., & Fan, X. (2014). Study on Method of Feature Selection in Speech Content Classification. International Journal of Advanced Computer Science and Applications, 5(4). https://doi.org/10.14569/IJACSA.2014.050412

An, Si, and Xinghua Fan. "Study on Method of Feature Selection in Speech Content Classification." International Journal of Advanced Computer Science and Applications, vol. 5, no. 4, 2014, https://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},
  volume    = {5},
  number    = {4},
  year      = {2014},
  publisher = {The Science and Information Organization},
  author    = {Si An and Xinghua Fan},
  doi       = {10.14569/IJACSA.2014.050412},
  url       = {https://doi.org/10.14569/IJACSA.2014.050412}
}

Open Access — licensed under a Creative Commons Attribution 4.0 International License. Unrestricted use, distribution, and reproduction in any medium, even commercially, as long as the original work is properly cited.

Call for Papers - Important Dates

Volume 17 No. 11, November 2026
Paper Submission Due October 25, 2026
Review Notification November 15, 2026
Publication Date November 30, 2026