SIMSAMU - A French medical dispatch dialog open dataset
We propose a French open medical dispatch dialogue dataset and an expert-validated schema of the medical dispatch dialogue based on unsupervised analysis. Notable gaps in how well speech recognition models generalize underscore the need for targeted, in-domain fine-tuning in this specialized application. SIMSAMU is designed to support this effort by serving as a benchmark for evaluating domain-adapted speech recognition and dialogue modeling strategies.
Authors
- Frédéric Lapostolle (ORCID: https://orcid.org/0000-0002-6624-6658)
- Gaël Guibon (ORCID: https://orcid.org/0000-0003-2420-9311)
- Ivan Lerner (ORCID: https://orcid.org/0000-0002-5466-1707)
- Olivier Birot
- Aimé Nun
Institutions
- Centre National de la Recherche Scientifique (FR)
- Inserm (FR)
- Université Paris Cité (FR)
- Sorbonne Université (FR)
- Université Sorbonne Paris Nord (FR)
- Sorbonne Paris Cité (FR)
- Centre de Recherche des Cordeliers (FR)
- Assistance Publique – Hôpitaux de Paris (FR)
- Hôpital Européen Georges-Pompidou (FR)
- Laboratoire de physique des lasers (FR)
- Laboratoire d'Informatique de Paris-Nord (FR)
Publication Details
- Journal
- Computer Methods and Programs in Biomedicine
- Published
- 2025-05-15
- DOI
- https://doi.org/10.1016/j.cmpb.2025.108857
- Primary Topic
- Topic Modeling
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Agence Nationale de la Recherche