NDLI: Iterative feature normalization for emotional speech detection

Content Provider	IEEE Xplore Digital Library
Author	Busso, C. Metallinou, A. Narayanan, S.S.
Copyright Year	2011
Description	Author affiliation: Speech Analysis and Interpretation Laboratory, Viterbi School of Engineering, University of Southern California, USA (Metallinou, A.; Narayanan, S.S.) \|\| Multimodal Signal Processing (MSP), Department of Electrical Engineering, The University of Texas at Dallas, USA (Busso, C.)
Abstract	Contending with signal variability due to source and channel effects is a critical problem in automatic emotion recognition. Any approach in mitigating these effects however has to be done so as to not compromise emotion-relevant information in the signal. A promising approach to this problem has been through feature normalization using features drawn from non-emotional (“neutral”) speech samples. This paper considers a scheme for minimizing the inter-speaker differences while still preserving the emotional discrimination of the acoustic features. This can be achieved by estimating the normalization parameters using only neutral speech, and then applying the coefficients to the entire corpus (including emotional set). Specifically, this paper introduces a feature normalization scheme that implements these ideas by iteratively detecting neutral speech and normalizing the features. As the approximation error of the normalization parameters is reduced, the accuracy of the emotion detection system increases. The accuracy of the proposed iterative approach, evaluated across three databases, is only 2.5% lower than the one trained with optimal normalization parameters, and 9.7% higher than the one trained without any normalization scheme.
Starting Page	5692
Ending Page	5695
File Size	270913
Page Count	4
File Format	PDF
ISBN	9781457705380
ISSN	15206149
e-ISBN	9781457705397
e-ISBN	9781457705373
DOI	10.1109/ICASSP.2011.5947652
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-05-22
Publisher Place	Czech Republic
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Speech Accuracy Databases Hidden Markov models Acoustics Emotion recognition Feature extraction feature normalization emotion recognition fundamental frequency emotions
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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