This paper presents the E- MIMIC project, an application that aims to eliminate non-inclusive, prejudiced language forms in administrative texts written in European countries, starting with those written in Romance languages. It presents a methodology based on discourse criteria inspired by French discourse analysis and used to label a corpus of institutional documents, which are used for the deep learning of neural networks. Deep Language Modelling architectures are exploited to automatically identify non-inclusive text snippets, suggest alternative forms, and produce inclusive text rephrasing. A preliminary evaluation conducted on a benchmark dataset in Italian shows promising results and encourages us to finalise the application and to implement it also for other languages, such as French.

L’analyse du discours et l’intelligence artificielle pour réaliser une écriture inclusive : le projet E- MIMIC

Rachele Raus;Michela Tonti;
2022

Abstract

This paper presents the E- MIMIC project, an application that aims to eliminate non-inclusive, prejudiced language forms in administrative texts written in European countries, starting with those written in Romance languages. It presents a methodology based on discourse criteria inspired by French discourse analysis and used to label a corpus of institutional documents, which are used for the deep learning of neural networks. Deep Language Modelling architectures are exploited to automatically identify non-inclusive text snippets, suggest alternative forms, and produce inclusive text rephrasing. A preliminary evaluation conducted on a benchmark dataset in Italian shows promising results and encourages us to finalise the application and to implement it also for other languages, such as French.
8e Congrès Mondial de Linguistique Française
1
15
Rachele Raus, Michela Tonti, Tania Cerquitelli, Luca Cagliero, Giuseppe Attanasio, Moreno La Quatra, Salvatore Greco
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/889304
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