Investigating analysis of speech content through text classification

Souraya Ezzat, Neamat El Gayar, Moustafa M. Ghanem

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

The field of Text Mining has evolved over the past years to analyze textual resources. However, it can be used in several other applications. In this research, we are particularly interested in performing text mining techniques on audio materials after translating them into texts in order to detect the speakers' emotions. We describe our overall methodology and present our experimental results. In particular, we focus on the different features selection and classification methods used. Our results show interesting conclusions opening up new horizons in the field, and suggest an emergence of promising future work yet to be discovered.

Original languageEnglish
Title of host publication2010 International Conference of Soft Computing and Pattern Recognition
PublisherIEEE
Pages105-110
Number of pages6
ISBN (Electronic)9781424478965
ISBN (Print)9781424478972
DOIs
Publication statusPublished - 13 Jan 2011
Event2010 International Conference of Soft Computing and Pattern Recognition - Cergy-Pontoise, France
Duration: 7 Dec 201010 Dec 2010

Conference

Conference2010 International Conference of Soft Computing and Pattern Recognition
Abbreviated titleSoCPaR 2010
CountryFrance
CityCergy-Pontoise
Period7/12/1010/12/10

Keywords

  • Audio and text mining
  • Sentiment analysis

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Computer Vision and Pattern Recognition

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  • Cite this

    Ezzat, S., El Gayar, N., & Ghanem, M. M. (2011). Investigating analysis of speech content through text classification. In 2010 International Conference of Soft Computing and Pattern Recognition (pp. 105-110). IEEE. https://doi.org/10.1109/SOCPAR.2010.5686000