• DocumentCode
    2037385
  • Title

    Investigating analysis of speech content through text classification

  • Author

    Ezzat, Souraya ; Gayar, N.E. ; Ghanem, Moustafa M.

  • Author_Institution
    Center for Inf. Sci., Nile Univ., Giza, Egypt
  • fYear
    2010
  • fDate
    7-10 Dec. 2010
  • Firstpage
    105
  • Lastpage
    110
  • 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.
  • Keywords
    audio streaming; audio systems; classification; data mining; speech recognition; text analysis; audio material; classification method; features selection; investigating analysis; speaker emotion; speech content; text classification; text mining; textual resource; Accuracy; Classification algorithms; Engines; Feature extraction; Speech; Speech recognition; Support vector machines; Audio and Text Mining; Sentiment Analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Soft Computing and Pattern Recognition (SoCPaR), 2010 International Conference of
  • Conference_Location
    Paris
  • Print_ISBN
    978-1-4244-7897-2
  • Type

    conf

  • DOI
    10.1109/SOCPAR.2010.5686000
  • Filename
    5686000