Magalie Ochs
LIS UMR 7020, Aix Marseille Université, Universit´e de Toulon, CNRS, France
Philippe Blache
LPL UMR 7309, Aix Marseille Université, Universit´e de Toulon, CNRS, France
Grégoire Montcheuil
LPL UMR 7309, Boréal Innovation, Aix Marseille Université, Universit´e de Toulon, CNRS, France
Jean-Marie Pergandi
ISM UMR 7287, Aix Marseille Université, Universit´e de Toulon, CNRS, France
Roxane
Bertrand
LPL UMR 7309, Aix Marseille Universit´e, Université de Toulon, CNRS, France
Jorane Saubesty
LPL UMR 7309, Aix Marseille Universit´e, Université de Toulon, CNRS, France
Daniel Francon
Institut Paoli-Calmettes (IPC), Marseille, France
Daniel Mestre
ISM UMR 7287, Aix Marseille Universit´e, Universit´e de Toulon, CNRS, France
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Published in: Selected papers from the CLARIN Annual Conference 2018, Pisa, 8-10 October 2018
Linköping Electronic Conference Proceedings 159:12, p. 113-120
Published: 2019-05-28
ISBN: 978-91-7685-034-3
ISSN: 1650-3686 (print), 1650-3740 (online)
The paper aims at presenting the Acorformed corpus composed of human-human and human-machine interactions in French in the specific context of training doctors to break bad news to patients. In the context of human-human interaction, an audiovisual corpus of interactions between doctors and actors playing the role of patients during real training sessions in French medical institutions have been collected and annotated. This corpus has been exploited to develop a platform to train doctors to break bad news with a virtual patient. The platform has been exploited to collect a corpus of human-virtual patient interactions annotated semi-automatically and collected in different virtual reality environments with different degree of immersion (PC, virtual reality headset and virtual reality room).
Multimodal corpora,
Multimodal annotation,
Virtual reality,
Embodied Conversational Agents,
Doctor-patient interaction
