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GIOVANNI PILATO

A Recurrent Deep Neural Network Model to measure Sentence Complexity for the Italian Language

  • Authors: Lo Bosco, G; Pilato, G; Schicchi D.
  • Publication year: 2019
  • Type: Contributo in atti di convegno pubblicato in volume
  • OA Link: http://hdl.handle.net/10447/366497

Abstract

Text simplification (TS) is a natural language processing task devoted to the modification of a text in such a way that the grammar and structure of the phrases is greatly simplified, preserving the underlying meaning and information contents. In this paper we give a contribution to the TS field presenting a deep neural network model able to detect the complexity of italian sentences. In particular, the system gives a score to an input text that identifies the confidence level during the decision making process and that could be interpreted as a measure of the sentence complexity. Experiments have been carried out on one public corpus of Italian texts created specifically for the task of TS. We have also provided a comparison of our model with a state of the art method used for the same purpose