A multi-modal dialogue analysis method for medical interviews based on design of interaction corpus.

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Bibliographic Details
Title:	A multi-modal dialogue analysis method for medical interviews based on design of interaction corpus.
Authors:	Koyama, Yuichi¹ ykoyama@nagoya-u.jp, Sawamoto, Yuichi², Hirano, Yasushi³ hirano@nagoya-u.jp, Kajita, Shoji³ kajita@nagoya-u.jp, Mase, Kenji¹ mase@nagoya-u.jp, Suzuki, Tomio⁴, Katsuyama, Kimiko⁵, Yamauchi, Kazunobu⁶
Source:	Personal & Ubiquitous Computing. Dec2010, Vol. 14 Issue 8, p767-778. 12p. 8 Diagrams, 5 Charts.
Subjects:	Dialogue analysis, Medical history taking, Physicians, Nonverbal communication, Indexes
Abstract:	We propose a multi-modal dialogue analysis method for medical interviews that hierarchically interprets nonverbal interaction patterns in a bottom-up manner and simultaneously visualizes the topic structure. Our method aims to provide physicians with the clues generally overlooked by conventional dialogue analysis to form a cycle of dialogue practice and analysis. We introduce a motif and a pattern cluster in the designs of the hierarchical indices of interaction and exploit the Jensen-Shannon divergence (JSD) metric to reduce the number of usable indices. We applied the proposed interpretation method of interaction patterns to develop a corpus of interviews. The results of a summary reading experiment confirmed the validity of the developed indices. Finally, we discussed the integrated analysis of the topic structure and a nonverbal summary. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	We propose a multi-modal dialogue analysis method for medical interviews that hierarchically interprets nonverbal interaction patterns in a bottom-up manner and simultaneously visualizes the topic structure. Our method aims to provide physicians with the clues generally overlooked by conventional dialogue analysis to form a cycle of dialogue practice and analysis. We introduce a motif and a pattern cluster in the designs of the hierarchical indices of interaction and exploit the Jensen-Shannon divergence (JSD) metric to reduce the number of usable indices. We applied the proposed interpretation method of interaction patterns to develop a corpus of interviews. The results of a summary reading experiment confirmed the validity of the developed indices. Finally, we discussed the integrated analysis of the topic structure and a nonverbal summary. [ABSTRACT FROM AUTHOR]
ISSN:	16174909
DOI:	10.1007/s00779-010-0289-5