@inproceedings{laleye-etal-2020-french,
title = "A {F}rench Medical Conversations Corpus Annotated for a Virtual Patient Dialogue System",
author = {Laleye, Fr{\'e}jus A. A. and
de Chalendar, Ga{\"e}l and
Blani{\'e}, Antonia and
Brouquet, Antoine and
Behnamou, Dan},
booktitle = "Proceedings of the 12th Language Resources and Evaluation Conference",
month = may,
year = "2020",
address = "Marseille, France",
publisher = "European Language Resources Association",
url = "https://aclanthology.org/2020.lrec-1.72",
pages = "574--580",
abstract = "Data-driven approaches for creating virtual patient dialogue systems require the availability of large data specific to the language,domain and clinical cases studied. Based on the lack of dialogue corpora in French for medical education, we propose an annotatedcorpus of dialogues including medical consultation interactions between doctor and patient. In this work, we detail the building processof the proposed dialogue corpus, describe the annotation guidelines and also present the statistics of its contents. We then conducted aquestion categorization task to evaluate the benefits of the proposed corpus that is made publicly available.",
language = "English",
ISBN = "979-10-95546-34-4",
}
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%0 Conference Proceedings
%T A French Medical Conversations Corpus Annotated for a Virtual Patient Dialogue System
%A Laleye, Fréjus A. A.
%A de Chalendar, Gaël
%A Blanié, Antonia
%A Brouquet, Antoine
%A Behnamou, Dan
%S Proceedings of the 12th Language Resources and Evaluation Conference
%D 2020
%8 may
%I European Language Resources Association
%C Marseille, France
%@ 979-10-95546-34-4
%G English
%F laleye-etal-2020-french
%X Data-driven approaches for creating virtual patient dialogue systems require the availability of large data specific to the language,domain and clinical cases studied. Based on the lack of dialogue corpora in French for medical education, we propose an annotatedcorpus of dialogues including medical consultation interactions between doctor and patient. In this work, we detail the building processof the proposed dialogue corpus, describe the annotation guidelines and also present the statistics of its contents. We then conducted aquestion categorization task to evaluate the benefits of the proposed corpus that is made publicly available.
%U https://aclanthology.org/2020.lrec-1.72
%P 574-580
Markdown (Informal)
[A French Medical Conversations Corpus Annotated for a Virtual Patient Dialogue System](https://aclanthology.org/2020.lrec-1.72) (Laleye et al., LREC 2020)
ACL