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
Link To Document :
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