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A Spoken Drug Prescription Dataset in French for Spoken Language Understanding

Proceedings of the Thirteenth International Conference on Language Resources and Evaluation (LREC 2022)

DOI:10.63317/5mg8x5t822yx

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 the 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 PxNLU. 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.

Details

Paper ID
lrec2022-main-109
Pages
pp. 1023-1031
BibKey
kocabiyikoglu-etal-2022-spoken
Editor
N/A
Publisher
European Language Resources Association (ELRA)
ISSN
2522-2686
ISBN
79-10-95546-38-2
Conference
Thirteenth Language Resources and Evaluation Conference
Location
Marseille, France
Date
20 June 2022 25 June 2022

Authors

  • AK

    Ali Can Kocabiyikoglu

  • FP

    François Portet

  • PG

    Prudence Gibert

  • HB

    Hervé Blanchon

  • JB

    Jean-Marc Babouchkine

  • GG

    Gaëtan Gavazzi

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