Attention-based Model for Evaluating the Complexity of Sentences in English Language

Giosue' Lo Bosco, Giovanni Pilato, Daniele Schicchi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

The automation of text complexity evaluation (ATCE) is an emerging problem which has been tackled bymeans of different methodologies. We present an effective deep learning- based solution which leverages both Recurrent Neural and the Attention mechanism. The developed system is capable of classifying sentences written in the English language by analysing their syntactical and lexical complexity. An accurate test phase has been carried out, and the system has been compared with a baseline tool based on the Support Vector Machine. This paper represents an extension of a previous deep learning model, which allows showing the suitability of Neural Networks to evaluate sentence complexity in two different languages: Italian and English.
Original languageEnglish
Title of host publication20TH IEEE MEDITERRANEAN ELETROTECHNICAL CONFERENCE Melecon 2020
Pages221-225
Number of pages5
Publication statusPublished - 2020

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Electrical and Electronic Engineering
  • Control and Optimization
  • Information Systems and Management
  • Energy Engineering and Power Technology

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