[2I5-OS-9a] Affective Computing(1/2)

[2I5-OS-9a-04] Speech Emotion Recognition using Topic Information

〇Mayuko Ozawa¹, Ryotaro Nagase¹, Takahiro Fukumori¹, Yoichi Yamashita¹ (1. Univ. of Ritsumeikan)

Keywords:Speech Emotion Recognition, Topic Information, Neural Network

In this paper, we analyze the impact of topic information on the performance of speech emotion recognition (SER). Conventional methods estimate emotions considering individuality, such as age and gender. However, there are factors, not limited to individuality, that influence the expression of emotions. For example, when people talk about the death of their friend, they may feel more sadness than anger and happiness. We propose two methods of SER considering the topic information. One of the proposed methods is using one-hot representation of the topic label. The other is utilizing the occurrence ratio of emotions in each topic. We experiment with the IEMOCAP corpus for recognizing emotions. As a result, the two methods performed equally or better than the baseline. These results show that topic information is effective on the performance of SER.