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Conference Paper
Ensemble Classifier based on Decision-Fusion of Multiple Models for Speech Emotion Recognition
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- Authors
- Kyoungju Noh, Jiyoun Lim, Seungeun Chung, Gague Kim, Hyuntae Jeong
- Issue Date
- 2018-10
- Citation
- International Conference on Information and Communication Technology Convergence (ICTC) 2018, pp.1246-1248
- Publisher
- IEEE
- Language
- English
- Type
- Conference Paper
- 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.
- KSP Keywords
- Categorical model, Multiple models, Speech Emotion recognition, ensemble classifiers, learning models