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Speech Emotion Recognition based on Voiced Emotion Unit
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 178 - Number 47 |
| Year of Publication: 2019 |
| Authors: Reda Elbarougy |
10.5120/ijca2019919355
|
Reda Elbarougy . Speech Emotion Recognition based on Voiced Emotion Unit. International Journal of Computer Applications. 178, 47 ( Sep 2019), 22-28. DOI=10.5120/ijca2019919355
Abstract
Speech emotion recognition (SER) system is becoming a very important tool for human-computer interaction. Previous studies in SER have been focused on utterance as one unit. They assumed that the emotional state is fixed during the utterance, although, the emotional state may change during the time even in one utterance. Therefore, using utterance as one unit is not suitable for this purpose especially for long utterances. The ultimate goal of this study is to find a novel emotion unit that can be used to improve SER accuracy. Therefore, different emotion units defined based on voiced segments are investigated. To find the optimal emotion unit, SER system based on support vector machine (SVM) classifier is used to evaluate each unit. The classification rate is used as a metric for the evaluation. To validate the proposed method, the Berlin database of emotional speech EMO-DB is used. The experimental results revealed that emotion unit that contains four voiced segments gives the highest recognition rate for SER. Moreover, the final emotional state of the whole utterance is determined by majority voting of emotional states of its units. It is found that the performance of the proposed method using voiced related emotion unit outperforms the conventional method using utterance as one unit.
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