Automatic Emotional Degree Labeling for Speakers’ Anger Utterance during Natural Japanese Dialog

Abstract

This paper describes a method of automatic emotional degree labeling for speaker’s anger utterances during natural Japanese dialog. First, we explain how to record anger utterance naturally appeared in natural Japanese dialog. Manual emotional degree labeling was conducted in advance to grade the utterances by a 6 Likert scale to obtain a correct anger degree. Then experiments of automatic anger degree estimation were conducted to label an anger degree with each utterance by its acoustic features. Also estimation experiments were conducted with speaker-dependent datasets to find out any influence of individual emotional expression on automatic emotional degree labeling. As a result, almost all the speaker’s models show higher adjusted R square so that those models are superior to the speaker-independent model in those estimation capabilities. However, a residual between automatic emotional degree and manual emotional degree (0.73) is equivalent to those of speaker’s models. There still has a possibility to label utterances with the speaker-independent model.

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