Abstract:
This paper proposes an ensemble classifier based on decision-fusion of multiple SER (Speech Emotion Recognition) models. The one of the multiple SER models used in this w...Show MoreMetadata
Abstract:
This paper proposes an ensemble classifier based on decision-fusion of multiple SER (Speech Emotion Recognition) models. The one of the multiple SER models used in this work is a typical categorical learning model for classifying the emotion labels, while the others are A/V (Arousal/Valence) models that recognize multiple A/V states based on the Russell's A/V emotion space. The evaluation performed in this work shows that the SER accuracy of the proposed ensemble classifier that combines each output of categorical model and A/V models is improved compare to the result when each SER model is applied separately.
Published in: 2018 International Conference on Information and Communication Technology Convergence (ICTC)
Date of Conference: 17-19 October 2018
Date Added to IEEE Xplore: 18 November 2018
ISBN Information:
Print on Demand(PoD) ISSN: 2162-1233