Recognition of emotional states in spoken dialogue with a robot

Kazunori Komatani*, Ryosuke Ito, Tatsuya Kawahara, Hiroshi G. Okuno

*この研究の対応する著者

研究成果: Conference contribution

3 被引用数 (Scopus)

抄録

For flexible interactions between a robot and humans, we address the issue of automatic recognition of human emotions during the interaction such as embarrassment, pleasure, and affinity. To construct classifiers of emotions, we used the dialogue data between a humanoid robot, Robovie, and children, which was collected with the WOZ (Wizard of Oz) method. Besides prosodic features extracted from a single utterance, characteristics specific to dialogues such as utterance intervals and differences with previous utterances were also used. We used the SVM (Support Vector Machine) as a classifier to recognize two temporary emotions such as embarrassment or pleasure, and the decision tree learning algorithm, C5.0, as a classifier to recognize persistent emotion, i.e. affinity. The accuracy of classification was 79% for embarrassment, 74% for pleasure, and 87% for affinity. The humanoid Robovie in which this emotion classification module was implemented demonstrated adaptive behaviors based on the emotions it recognized.

本文言語English
ホスト出版物のタイトルLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
編集者B. Orchard, C. Yang, M. Ali
ページ413-423
ページ数11
3029
出版ステータスPublished - 2004
外部発表はい
イベント17th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2004 - Ottowa, Ont., Canada
継続期間: 2004 5 172004 5 20

Other

Other17th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2004
国/地域Canada
CityOttowa, Ont.
Period04/5/1704/5/20

ASJC Scopus subject areas

  • ハードウェアとアーキテクチャ

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