AlloSat: A New Call Center French Corpus for Satisfaction and Frustration Analysis

Manon Macary, Marie Tahon, Yannick Estève, Anthony Rousseau


Abstract
We present a new corpus, named AlloSat, composed of real-life call center conversations in French that is continuously annotated in frustration and satisfaction. This corpus has been set up to develop new systems able to model the continuous aspect of semantic and paralinguistic information at the conversation level. The present work focuses on the paralinguistic level, more precisely on the expression of emotions. In the call center industry, the conversation usually aims at solving the caller’s request. As far as we know, most emotional databases contain static annotations in discrete categories or in dimensions such as activation or valence. We hypothesize that these dimensions are not task-related enough. Moreover, static annotations do not enable to explore the temporal evolution of emotional states. To solve this issue, we propose a corpus with a rich annotation scheme enabling a real-time investigation of the axis frustration / satisfaction. AlloSat regroups 303 conversations with a total of approximately 37 hours of audio, all recorded in real-life environments collected by Allo-Media (an intelligent call tracking company). First regression experiments, with audio features, show that the evolution of frustration / satisfaction axis can be retrieved automatically at the conversation level.
Anthology ID:
2020.lrec-1.197
Volume:
Proceedings of the 12th Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Venue:
LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
1590–1597
Language:
English
URL:
https://aclanthology.org/2020.lrec-1.197
DOI:
Bibkey:
Cite (ACL):
Manon Macary, Marie Tahon, Yannick Estève, and Anthony Rousseau. 2020. AlloSat: A New Call Center French Corpus for Satisfaction and Frustration Analysis. In Proceedings of the 12th Language Resources and Evaluation Conference, pages 1590–1597, Marseille, France. European Language Resources Association.
Cite (Informal):
AlloSat: A New Call Center French Corpus for Satisfaction and Frustration Analysis (Macary et al., LREC 2020)
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PDF:
https://aclanthology.org/2020.lrec-1.197.pdf