Monolingual sentence matching for text simplification
Computation and Language
2018-09-25 v1
Abstract
This work improves monolingual sentence alignment for text simplification, specifically for text in standard and simple Wikipedia. We introduce a convolutional neural network structure to model similarity between two sentences. Due to the limitation of available parallel corpora, the model is trained in a semi-supervised way, by using the output of a knowledge-based high performance aligning system. We apply the resulting similarity score to rescore the knowledge-based output, and adapt the model by a small hand-aligned dataset. Experiments show that both rescoring and adaptation improve the performance of knowledge-based method.
Cite
@article{arxiv.1809.08703,
title = {Monolingual sentence matching for text simplification},
author = {Yonghui Huang and Yunhui Li and Yi Luan},
journal= {arXiv preprint arXiv:1809.08703},
year = {2018}
}