Sentence Simplification using Syntactic Parse trees

Abstract

Text simplification is one of the domains in Natural Language Processing which offers great promise for exploration. Simplifying sentences offer better results, as compared dealing with complex/compound sentences, in many language processing applications as well. Recently, Neural Networks have been used in simplifying texts, be it by state of the art LSTM's and GRU cells or by Reinforcement learning models. In contrast, in this work, we present a classical approach consisting of two separate algorithms, for simplification of complex and compound sentences to their corresponding simple forms.