Ponce-Lopez, Vctor;
Escalera, Sergio;
Baro, Xavier;
(2013)
Multi-modal Social Signal Analysis for Predicting Agreement in Conversation Settings.
In:
ICMI '13: Proceedings of the 15th ACM on International conference on multimodal interaction.
(pp. pp. 495-501).
Association for Computing Machinery: NY, USA.
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Abstract
In this paper we present a non-invasive ambient intelligence framework for the analysis of non-verbal communication applied to conversational settings. In particular, we apply feature extraction techniques to multi-modal audio-RGB-depth data. We compute a set of behavioral indicators that define communicative cues coming from the fields of psychology and observational methodology. We test our methodology over data captured in victim-offender mediation scenarios. Using different state-of-the-art classification approaches, our system achieve upon 75% of recognition predicting agreement among the parts involved in the conversations, using as ground truth the experts opinions.
| Type: | Proceedings paper |
|---|---|
| Title: | Multi-modal Social Signal Analysis for Predicting Agreement in Conversation Settings |
| Event: | 15th ACM International Conference on Multimodal Interaction (ICMI) |
| Location: | Sydney, AUSTRALIA |
| Dates: | 9 Dec 2013 - 13 Dec 2013 |
| ISBN-13: | 9781450321297 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1145/2522848.2532594 |
| Publisher version: | https://doi.org/10.1145/2522848.2532594 |
| Language: | English |
| Additional information: | This version is the author-accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Computer Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10164868 |
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