Investigating analysis of speech content through text classification

Souraya Ezzat; Neamat El Gayar; Moustafa M. Ghanem

doi:10.1109/SOCPAR.2010.5686000

Investigating analysis of speech content through text classification

Souraya Ezzat^*, Neamat El Gayar, Moustafa M. Ghanem

^*Corresponding author for this work

School of Mathematical & Computer Sciences

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 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 language	English
Title of host publication	2010 International Conference of Soft Computing and Pattern Recognition
Publisher	IEEE
Pages	105-110
Number of pages	6
ISBN (Electronic)	9781424478965
ISBN (Print)	9781424478972
DOIs	https://doi.org/10.1109/SOCPAR.2010.5686000
Publication status	Published - 13 Jan 2011
Event	2010 International Conference of Soft Computing and Pattern Recognition - Cergy-Pontoise, France Duration: 7 Dec 2010 → 10 Dec 2010

Conference

Conference	2010 International Conference of Soft Computing and Pattern Recognition
Abbreviated title	SoCPaR 2010
Country/Territory	France
City	Cergy-Pontoise
Period	7/12/10 → 10/12/10

Keywords

Audio and text mining
Sentiment analysis

ASJC Scopus subject areas

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

Access to Document

10.1109/SOCPAR.2010.5686000

Cite this

@inproceedings{8cbfa3fb703e4fdaa0a3ff38fe48a0b4,

title = "Investigating analysis of speech content through text classification",

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 and text mining, Sentiment analysis",

author = "Souraya Ezzat and {El Gayar}, Neamat and Ghanem, {Moustafa M.}",

year = "2011",

month = jan,

day = "13",

doi = "10.1109/SOCPAR.2010.5686000",

language = "English",

isbn = "9781424478972",

pages = "105--110",

booktitle = "2010 International Conference of Soft Computing and Pattern Recognition",

publisher = "IEEE",

address = "United States",

note = "2010 International Conference of Soft Computing and Pattern Recognition, SoCPaR 2010 ; Conference date: 07-12-2010 Through 10-12-2010",

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TY - GEN

T1 - Investigating analysis of speech content through text classification

AU - Ezzat, Souraya

AU - El Gayar, Neamat

AU - Ghanem, Moustafa M.

PY - 2011/1/13

Y1 - 2011/1/13

N2 - 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.

AB - 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.

KW - Audio and text mining

KW - Sentiment analysis

UR - http://www.scopus.com/inward/record.url?scp=79951487280&partnerID=8YFLogxK

U2 - 10.1109/SOCPAR.2010.5686000

DO - 10.1109/SOCPAR.2010.5686000

M3 - Conference contribution

AN - SCOPUS:79951487280

SN - 9781424478972

SP - 105

EP - 110

BT - 2010 International Conference of Soft Computing and Pattern Recognition

PB - IEEE

T2 - 2010 International Conference of Soft Computing and Pattern Recognition

Y2 - 7 December 2010 through 10 December 2010

ER -

Investigating analysis of speech content through text classification

Abstract

Conference

Keywords

ASJC Scopus subject areas

Access to Document

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