The importance of sharing patient-generated clinical speech and language data - Archive ouverte HAL Accéder directement au contenu
Communication Dans Un Congrès Année : 2019

The importance of sharing patient-generated clinical speech and language data

Résumé

Increased access to large datasets has driven progress in NLP. However, most computational studies of clinically-validated, patient-generated speech and language involve very few datapoints, as such data are difficult (and expensive) to collect. In this position paper, we argue that we must find ways to promote data sharing across research groups, in order to build datasets of a more appropriate size for NLP and machine learning analysis. We review the benefits and challenges of sharing clinical language data, and suggest several concrete actions by both clinical and NLP researchers to encourage multi-site and multidisciplinary data sharing. We also propose the creation of a collaborative data sharing platform , to allow NLP researchers to take a more active responsibility for data transcription, annotation , and curation.
Fichier principal
Vignette du fichier
W19-3007.pdf (171.16 Ko) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-02339141 , version 1 (07-11-2022)

Identifiants

Citer

Kathleen C Fraser, Nicklas Linz, Hali Lindsay, Alexandra König. The importance of sharing patient-generated clinical speech and language data. CLPsyc 2019 - Sixth Workshop on Computational Linguistics and Clinical Psychology, Jun 2019, Minneapolis, Minnesota, United States. pp.55 - 61, ⟨10.18653/v1/W19-3007⟩. ⟨hal-02339141⟩
24 Consultations
27 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More