Abstract
The detection of conflict cues in call center interactions may be related to the quality assessment of the services provided, since these cues reveal both speakers’ emotional states and positioning as expressed through complaining and identifying problematic issues on the one hand and managing requests or resolving problems on the other hand. This paper describes a set of emotional and conversational cues associated to conflict as well as a machine learning approach to classify emotional speech units occurring in a call center dataset by employing emotion labels as well as automatically extracted acoustic and additional context-related features.
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Acknowledgments
The research leading to these results has been partially funded by POLYTROPON project (KRIPIS-GSRT, MIS: 448306). Also, the participation to Dagstuhl Seminar 13451 “Computational Audio Analysis” held from Nov 3 to 8, 2013, in Wadern, Germany, inspired Anna Esposito to contribute to this work.
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Koutsombogera, M. et al. (2015). Conflict Cues in Call Center Interactions. In: D'Errico, F., Poggi, I., Vinciarelli, A., Vincze, L. (eds) Conflict and Multimodal Communication. Computational Social Sciences. Springer, Cham. https://doi.org/10.1007/978-3-319-14081-0_20
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DOI: https://doi.org/10.1007/978-3-319-14081-0_20
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