Text Readability Assessment for Second Language Learners

Understand

This paper addresses the task of readability assessment for the texts aimed at second language (L2) learners.

• One of the major challenges in this task is the lack of significantly sized level-annotated data.
• For the present work, we collected a dataset of CEFR-graded texts tailored for learners of English as an L2 and investigated text readability assessment for both native and L2 learners.
• We applied a generalization method to adapt models trained on larger native corpora to estimate text readability for learners, and explored domain adaptation and self-learning techniques to make use of the native data to improve system performance on the limited L2 data.