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Ensemble feature selection for domain adaptation in speech emotion recognition

Abstract: 

When emotion recognition systems are used in new domains, the classification performance usually drops due to mismatches between training and testing conditions. Annotations of new data in the new domain is expensive and time demanding. Therefore, it is important to design strategies that efficiently use limited amount of new data to improve the robustness of the classification system. The use of ensembles is an attractive solution, since they can be built to perform well across different mismatches. The key challenge is to create ensembles that are diverse. This paper proposes the use of active learning along with feature selection to build a diverse ensemble that performs well in the new domain. The diversity and accuracy of the ensemble are achieved by (1) training emotional classifiers with bias toward specific emotions, (2) eliminating overlap in the feature sets of the ensemble, and (3) conducting feature selection by maximizing the performance over the new labeled data. We study various data selection criteria, and different sample sizes to determine the best approach toward building a stable diverse ensemble that generalize well on new domains.

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Paper Details

Authors:
Mohammed Abdelwahab, Carlos Busso
Submitted On:
20 May 2020 - 10:34am
Short Link:
Type:
Presentation Slides
Event:
Presenter's Name:
Mohammed Abdelwahab
Document Year:
2017
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Document Files

ICASSP_2017_Ensemble.pdf

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[1] Mohammed Abdelwahab, Carlos Busso, "Ensemble feature selection for domain adaptation in speech emotion recognition", IEEE SigPort, 2020. [Online]. Available: http://sigport.org/5415. Accessed: Jun. 06, 2020.
@article{5415-20,
url = {http://sigport.org/5415},
author = {Mohammed Abdelwahab; Carlos Busso },
publisher = {IEEE SigPort},
title = {Ensemble feature selection for domain adaptation in speech emotion recognition},
year = {2020} }
TY - EJOUR
T1 - Ensemble feature selection for domain adaptation in speech emotion recognition
AU - Mohammed Abdelwahab; Carlos Busso
PY - 2020
PB - IEEE SigPort
UR - http://sigport.org/5415
ER -
Mohammed Abdelwahab, Carlos Busso. (2020). Ensemble feature selection for domain adaptation in speech emotion recognition. IEEE SigPort. http://sigport.org/5415
Mohammed Abdelwahab, Carlos Busso, 2020. Ensemble feature selection for domain adaptation in speech emotion recognition. Available at: http://sigport.org/5415.
Mohammed Abdelwahab, Carlos Busso. (2020). "Ensemble feature selection for domain adaptation in speech emotion recognition." Web.
1. Mohammed Abdelwahab, Carlos Busso. Ensemble feature selection for domain adaptation in speech emotion recognition [Internet]. IEEE SigPort; 2020. Available from : http://sigport.org/5415