Using speech data to recognize emotion in human gait

Angelica Lim*, Hiroshi G. Okuno

*この研究の対応する著者

研究成果: Conference contribution

10 被引用数 (Scopus)

抄録

Robots that can recognize emotions can improve humans' mental health by providing empathy and social communication. Emotion recognition by robots is challenging because unlike in human-computer environments, facial information is not always available. Instead, our method proposes using speech and gait analysis to recognize human emotion. Previous research suggests that the dynamics of emotional human speech also underlie emotional gait (walking). We investigate the possibility of combining these two modalities via perceptually common parameters: Speed, Intensity, irRegularity, and Extent (SIRE). We map low-level features to this 4D cross-modal emotion space and train a Gaussian Mixture Model using independent samples from both voice and gait. Our results show that a single, modality-mixed trained model can perform emotion recognition for both modalities. Most interestingly, recognition of emotion in gait using a model trained uniquely on speech data gives comparable results to a model trained on gait data alone, providing evidence for a common underlying model for emotion across modalities.

本文言語English
ホスト出版物のタイトルLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ページ52-64
ページ数13
7559 LNCS
DOI
出版ステータスPublished - 2012
外部発表はい
イベント3rd International Workshop on Human Behavior Understanding, HBU 2012 - Vilamoura
継続期間: 2012 10 72012 10 7

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
7559 LNCS
ISSN(印刷版)03029743
ISSN(電子版)16113349

Other

Other3rd International Workshop on Human Behavior Understanding, HBU 2012
CityVilamoura
Period12/10/712/10/7

ASJC Scopus subject areas

  • コンピュータ サイエンス(全般)
  • 理論的コンピュータサイエンス

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