A Spoken Drug Prescription Dataset in French for Spoken Language Understanding - Archive ouverte HAL
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Communication dans un congrès

A Spoken Drug Prescription Dataset in French for Spoken Language Understanding

Ali Can Kocabiyikoglu 1, 2 François Portet 1 Prudence Gibert 3 Hervé Blanchon 1 Jean-Marc Babouchkine 2 Gaëtan Gavazzi 4, 3 
4 TIMC-GREPI - Groupe de Recherche et d’Étude du Processus Inflammatoire
TIMC - Translational Innovation in Medicine and Complexity / Recherche Translationnelle et Innovation en Médecine et Complexité - UMR 5525 : EA2938
Abstract : Spoken medical dialogue systems are increasingly attracting interest to enhance access to healthcare services and improve quality and traceability of patient care. In this paper, we focus on medical drug prescriptions acquired on smartphones through spoken dialogue. Such systems would facilitate the traceability of care and would free clinicians' time. However, there is a lack of speech corpora to develop such systems since most of the related corpora are in text form and in English. To facilitate the research and development of spoken medical dialogue systems, we present, to the best of our knowledge, the first spoken medical drug prescriptions corpus, named PxSLU. It contains 4 hours of transcribed and annotated dialogues of drug prescriptions in French acquired through an experiment with 55 participants experts and non-experts in prescriptions. We also present some experiments that demonstrate the interest of this corpus for the evaluation and development of medical dialogue systems.
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Communication dans un congrès
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https://hal.archives-ouvertes.fr/hal-03727237
Contributeur : François Portet Connectez-vous pour contacter le contributeur
Soumis le : mardi 19 juillet 2022 - 10:23:19
Dernière modification le : mardi 27 septembre 2022 - 13:52:04

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  • HAL Id : hal-03727237, version 1
  • ARXIV : 2207.08292

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Ali Can Kocabiyikoglu, François Portet, Prudence Gibert, Hervé Blanchon, Jean-Marc Babouchkine, et al.. A Spoken Drug Prescription Dataset in French for Spoken Language Understanding. LREC 2022, Jun 2022, Marseille, France. ⟨hal-03727237⟩

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