NDLI: Automatic detection of interaction groups

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Automatic detection of interaction groups

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Automatic detection of interaction groups

Content Provider	ACM Digital Library
Author	Brdiczka, Oliver Maisonnasse, Jérôme Reignier, Patrick
Abstract	This paper addresses the problem of detecting interaction groups in an intelligent environment. To understand human activity, we need to identify human actors and their interpersonal links. An interaction group can be seen as basic entity, within which individuals collaborate in order to achieve a common goal. In this regard, the dynamic change of interaction group configuration, i.e. the split and merge of interaction groups, can be seen as indicator of new activities. Our approach takes speech activity detection of individuals forming interaction groups as input. A classical HMM-based approach learning different HMM for the different group configurations did not produce promising results. We propose an approach for detecting interaction group configurations based on the assumption that conversational turn taking is synchronized inside groups. The proposed detector is based on one HMM constructed upon conversational hypotheses. The approach shows good results and thus confirms our conversational hypotheses.
Starting Page	32
Ending Page	36
Page Count	5
File Format	PDF
ISBN	1595930280
DOI	10.1145/1088463.1088473
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2005-10-04
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Intelligent environment Conversational analysis Clustering interaction groups Ubiquitous computing Speech detection Hidden markov model
Content Type	Text
Resource Type	Article

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