@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},
editor = "Calzolari, Nicoletta and
B{\'e}chet, Fr{\'e}d{\'e}ric and
Blache, Philippe and
Choukri, Khalid and
Cieri, Christopher and
Declerck, Thierry and
Goggi, Sara and
Isahara, Hitoshi and
Maegaard, Bente and
Mariani, Joseph and
Mazo, H{\'e}l{\`e}ne and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Twelfth 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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<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.</abstract>
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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
%Y Calzolari, Nicoletta
%Y Béchet, Frédéric
%Y Blache, Philippe
%Y Choukri, Khalid
%Y Cieri, Christopher
%Y Declerck, Thierry
%Y Goggi, Sara
%Y Isahara, Hitoshi
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Mazo, Hélène
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Twelfth 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