6533b860fe1ef96bd12c2c9b
RESEARCH PRODUCT
A recurrent deep neural network model to measure sentence complexity for the Italian Language
G. Lo BoscoG. PilatoDaniele Schicchisubject
Deep Neural NetworksText Simplification Natural Language Processing Deep Neural NetworksSettore INF/01 - InformaticaComputingMethodologies_DOCUMENTANDTEXTPROCESSINGAutomatic Text Complexity EvaluationNLPdescription
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.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2019-01-01 |