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| Content Provider | Springer Nature Link |
|---|---|
| Author | Pesarin, Anna Cristani, Marco Muri, Vittorio Vinciarelli, Alessandro |
| Copyright Year | 2011 |
| Abstract | This study proposes a semi-automatic approach aimed at detecting conflict in conversations. The approach is based on statistical techniques capable of identifying turn-organization regularities associated with conflict. The only manual step of the process is the segmentation of the conversations into turns (time intervals during which only one person talks) and overlapping speech segments (time intervals during which several persons talk at the same time). The rest of the process takes place automatically and the results show that conflictual exchanges can be detected with Precision and Recall around 70% (the experiments have been performed over 6 h of political debates). The approach brings two main benefits: the first is the possibility of analyzing potentially large amounts of conversational data with a limited effort, the second is that the model parameters provide indications on what turn-regularities are most likely to account for the presence of conflict. |
| Starting Page | 533 |
| Ending Page | 540 |
| Page Count | 8 |
| File Format | |
| ISSN | 16124782 |
| Journal | Cognitive Processing |
| Volume Number | 13 |
| Issue Number | 2 |
| e-ISSN | 16124790 |
| Language | English |
| Publisher | Springer-Verlag |
| Publisher Date | 2011-10-19 |
| Publisher Place | Berlin, Heidelberg |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Social signal processing Generative score space Conflict detection turn-organization Artificial Intelligence (incl. Robotics) Behavioural Sciences Neurosciences |
| Content Type | Text |
| Resource Type | Article |
| Subject | Experimental and Cognitive Psychology Artificial Intelligence Cognitive Neuroscience Medicine |
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