Abstract
The study presented in this paper deals with the modelling of extreme emotions occurring in abnormal situations. The aimed application is civil safety and surveillance in the public places in particular. A corpus of fiction (SAFE Corpus) is selected illustrating rich and varied contexts with the presence of extreme emotions, mainly fear. An annotation strategy adapted to the application is then developed, with both generic and specific descriptors. Finally, a detection system of fear emotions based on acoustic cues is implemented to carry out an evaluation. On the one hand the system is robust to context changes. On the other hand, the influence of multimodal annotation is minor. Results obtained with the various protocols are similar : fear is recognized with 67% of success.
| Original language | French |
|---|---|
| Pages (from-to) | 529-551 |
| Number of pages | 23 |
| Journal | Revue d'Intelligence Artificielle |
| Volume | 20 |
| Issue number | 4-5 |
| DOIs | |
| Publication status | Published - 1 Jan 2006 |
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