@inproceedings{liu-etal-2024-meddialog,
title = "{M}ed{D}ialog-{FR}: A {F}rench Version of the {M}ed{D}ialog Corpus for Multi-label Classification and Response Generation Related to Women{'}s Intimate Health",
author = "Liu, Xingyu and
Segonne, Vincent and
Mannion, Aidan and
Schwab, Didier and
Goeuriot, Lorraine and
Portet, Fran{\c{c}}ois",
editor = "Demner-Fushman, Dina and
Ananiadou, Sophia and
Thompson, Paul and
Ondov, Brian",
booktitle = "Proceedings of the First Workshop on Patient-Oriented Language Processing (CL4Health) @ LREC-COLING 2024",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.cl4health-1.21",
pages = "173--183",
abstract = "This article presents MedDialog-FR, a large publicly available corpus of French medical conversations for the medical domain. Motivated by the lack of French dialogue corpora for data-driven dialogue systems and the paucity of available information related to women{'}s intimate health, we introduce an annotated corpus of question-and-answer dialogues between a real patient and a real doctor concerning women{'}s intimate health. The corpus is composed of about 20,000 dialogues automatically translated from the English version of MedDialog-EN. The corpus test set is composed of 1,400 dialogues that have been manually post-edited and annotated with 22 categories from the UMLS ontology. We also fine-tuned state-of-the-art reference models to automatically perform multi-label classification and response generation to give an initial performance benchmark and highlight the difficulty of the tasks.",
}
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<abstract>This article presents MedDialog-FR, a large publicly available corpus of French medical conversations for the medical domain. Motivated by the lack of French dialogue corpora for data-driven dialogue systems and the paucity of available information related to women’s intimate health, we introduce an annotated corpus of question-and-answer dialogues between a real patient and a real doctor concerning women’s intimate health. The corpus is composed of about 20,000 dialogues automatically translated from the English version of MedDialog-EN. The corpus test set is composed of 1,400 dialogues that have been manually post-edited and annotated with 22 categories from the UMLS ontology. We also fine-tuned state-of-the-art reference models to automatically perform multi-label classification and response generation to give an initial performance benchmark and highlight the difficulty of the tasks.</abstract>
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%0 Conference Proceedings
%T MedDialog-FR: A French Version of the MedDialog Corpus for Multi-label Classification and Response Generation Related to Women’s Intimate Health
%A Liu, Xingyu
%A Segonne, Vincent
%A Mannion, Aidan
%A Schwab, Didier
%A Goeuriot, Lorraine
%A Portet, François
%Y Demner-Fushman, Dina
%Y Ananiadou, Sophia
%Y Thompson, Paul
%Y Ondov, Brian
%S Proceedings of the First Workshop on Patient-Oriented Language Processing (CL4Health) @ LREC-COLING 2024
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F liu-etal-2024-meddialog
%X This article presents MedDialog-FR, a large publicly available corpus of French medical conversations for the medical domain. Motivated by the lack of French dialogue corpora for data-driven dialogue systems and the paucity of available information related to women’s intimate health, we introduce an annotated corpus of question-and-answer dialogues between a real patient and a real doctor concerning women’s intimate health. The corpus is composed of about 20,000 dialogues automatically translated from the English version of MedDialog-EN. The corpus test set is composed of 1,400 dialogues that have been manually post-edited and annotated with 22 categories from the UMLS ontology. We also fine-tuned state-of-the-art reference models to automatically perform multi-label classification and response generation to give an initial performance benchmark and highlight the difficulty of the tasks.
%U https://aclanthology.org/2024.cl4health-1.21
%P 173-183
Markdown (Informal)
[MedDialog-FR: A French Version of the MedDialog Corpus for Multi-label Classification and Response Generation Related to Women’s Intimate Health](https://aclanthology.org/2024.cl4health-1.21) (Liu et al., CL4Health-WS 2024)
ACL