Pushing on Text Readability Assessment: A Transformer Meets Handcrafted Linguistic Features

1 code implementation • EMNLP 2021 • Bruce W. Lee, Yoo Sung Jang, Jason Hyung-Jong Lee

We report two essential improvements in readability assessment: 1. three novel features in advanced semantics and 2. the timely evidence that traditional ML models (e. g. Random Forest, using handcrafted features) can combine with transformers (e. g. RoBERTa) to augment model performance.

Text Classification