In this paper, we consider sentence simplification as a special form of translation with the complex sentence as the source and the simple sentence as the target. We propose a Tree-based Simplification Model (TSM), which, to our knowledge, is the first statistical simplification model covering splitting, dropping, reordering and substitution integrally. We also describe an efficient method to train our model with a large-scale parallel dataset obtained from the Wikipedia and Simple Wikipedia. The evaluation shows that our model achieves better readability scores than a set of baseline systems.
Sentence Simplification For statistical modeling, REF proposed a tree-based sentence simplification model drawing inspiration from statistical machine translation.
A Monolingual Tree-based Translation Model for Sentence Simplification
COLING
Computer Science