Acoustic emotion recognition has been an active research area. This paper presents a new Chinese corpus of emotionally colored conversations. Two discrete 3-point scaled emotion primitives are used to describe emotions, namely valence and arousal. Acoustic feature extraction is carried out using OpenSMILE toolkit. For the estimation of these primitives, Support Vector Machine (SVM) is used for the classification task. Preliminary classification results show the effectiveness of the proposed method.
|Title of host publication||IEEE international conference on security, pattern analysis, and cybernetics|
|Publication status||Published - 2017|