Prudence Gibert


2022

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A Spoken Drug Prescription Dataset in French for Spoken Language Understanding
Ali Can Kocabiyikoglu | François Portet | Prudence Gibert | Hervé Blanchon | Jean-Marc Babouchkine | Gaëtan Gavazzi
Proceedings of the Thirteenth Language Resources and Evaluation Conference

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.