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| Content Provider | ACM Digital Library |
|---|---|
| Author | Jérôme, Maisonnasse Oliver, Brdiczka |
| Abstract | This work brings a new perception to intelligent environments for human activity recognition. To understand human activities, we need to differentiate users concerned and their interpersonal links. We propose a new group interaction detection tool based on an assumption that conversational turn taking is synchronized inside groups. We assess HMM-based and algorithmic approaches to build a detector which is able to segment interaction groups from speech detection. Both approaches show good results thus confirm the conversational hypothesis. |
| Starting Page | 201 |
| Ending Page | 204 |
| Page Count | 4 |
| File Format | |
| ISBN | 1595931724 |
| DOI | 10.1145/1102613.1102653 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2005-05-31 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Conversationnal analysis Groups of interaction clustering Intelligent environment Ubiquitous computing Speech detection Markov model |
| Content Type | Text |
| Resource Type | Article |
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