Classification automatique de dict\'ees selon leur niveau de difficult\'e de compr\'ehension et orthographique (Automatic classification of dictations according to their complexity for comprehension and writing production)

JEPTALNRECITAL 2016 Adeline M{\"u}llerThomas FrancoisSophie RoekhautCedrick Fairon

Cet article pr{\'e}sente une approche visant {\`a} {\'e}valuer automatiquement la difficult{\'e} de dict{\'e}es en vue de les int{\'e}grer dans une plateforme d{'}apprentissage de l{'}orthographe. La particularit{\'e} de l{'}exercice de la dict{\'e}e est de devoir percevoir du code oral et de le retranscrire via le code {\'e}crit... (read more)

PDF Abstract

Code


No code implementations yet. Submit your code now

Tasks


Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper


METHOD TYPE
🤖 No Methods Found Help the community by adding them if they're not listed; e.g. Deep Residual Learning for Image Recognition uses ResNet