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

Giosue' Lo Bosco, Giovanni Pilato, Daniele Schicchi

Risultato della ricerca: Conference contribution

6 Citazioni (Scopus)

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 methodused for the same purpose
Lingua originaleEnglish
Titolo della pubblicazione ospiteAIC 2018, Artificial Intelligence and Cognition 2018 - Proceedings of the 6th International Workshop on Artificial Intelligence and Cognition
Pagine90-97
Numero di pagine8
Stato di pubblicazionePublished - 2019

Serie di pubblicazioni

NomeCEUR WORKSHOP PROCEEDINGS

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

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