Erroneous Coordinated Sentences Detection in French Students’ Writings - Archive ouverte HAL Accéder directement au contenu
Chapitre D'ouvrage Année : 2021

Erroneous Coordinated Sentences Detection in French Students’ Writings

Laura Noreskal

Résumé

This paper presents the development stages of an NLP device to be used to improve students’ skills in French academic writing. Among various relevant difficulties, we focus on coordinating constructions that include or not ellipsis. We develop a tool to detect errors automatically in coordinated sentences from a corpus composed of erroneous and correct sentences. We use a deep learning approach based on the French CamemBERT model. To find the best learning environment for the classification task, we show the results obtained from training and testing datasets with different proportions of erroneous and correct sentences.
Fichier non déposé

Dates et versions

hal-03697928 , version 1 (17-06-2022)

Identifiants

Citer

Laura Noreskal, Iris Eshkol-Taravella, Marianne Desmets. Erroneous Coordinated Sentences Detection in French Students’ Writings. Advances in Computational Collective Intelligence, 1463, Springer International Publishing, pp.586-596, 2021, Communications in Computer and Information Science, ⟨10.1007/978-3-030-88113-9_47⟩. ⟨hal-03697928⟩
34 Consultations
1 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More