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Cited by 655

Toward detecting emotions in spoken dialogs

Chul Min Lee, Narayanan, S.S.·2005·IEEE Transactions on Speech and Audio Processing
DOI 10.1109/tsa.2004.838534
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Abstract

The importance of automatically recognizing emotions from human speech has grown with the increasing role of spoken language interfaces in human-computer interaction applications. This paper explores the detection of domain-specific emotions using language and discourse information in conjunction with acoustic correlates of emotion in speech signals. The specific focus is on a case study of detecting negative and non-negative emotions using spoken language data obtained from a call center application. Most previous studies in emotion recognition have used only the acoustic information contained in speech. In this paper, a combination of three sources of information-acoustic, lexical, and discourse-is used for emotion recognition. To capture emotion information at the language level, an information-theoretic notion of emotional salience is introduced. Optimization of the acoustic correlates of emotion with respect to classification error was accomplished by investigating different feature sets obtained from feature selection, followed by principal component analysis. Experimental results on our call center data show that the best results are obtained when acoustic and language information are combined. Results show that combining all the information, rather than using only acoustic information, improves emotion classification by 40.7% for males and 36.4% for females (linear discriminant classifier used for acoustic information).

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  • The information channels (keystroke dynamics, written/oral content, and facial video) synergistically support investigations into participant emotions triggered by experimental stressors.

    “They combine keystroke dynamics, written/oral content, and facial video. These information channels synergistically support investigations into participant emotions9–12, triggered by the experimental stressors.”

    From Stress and productivity patterns of interrupted, synergistic, and antagonistic office activities (2019) · cites this paper as [11]

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Authors
Lee, C. M., & Narayanan, S. S.
Venue
IEEE Transactions on Speech and Audio Processing
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2005-03
Volume
13
Issue
2
Pages
293-303
ISSN
1063-6676
DOI
10.1109/tsa.2004.838534
Cited by
655
References
0
Licence
ieeexplore.ieee.org/Xplorehelp/downloads/license-information/IEEE.html (vor)

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