SOTAVerified

Gender-Aware Reinflection using Linguistically Enhanced Neural Models

2020-12-01GeBNLP (COLING) 2020Code Available0· sign in to hype

Bashar Alhafni, Nizar Habash, Houda Bouamor

Code Available — Be the first to reproduce this paper.

Reproduce

Code

Abstract

In this paper, we present an approach for sentence-level gender reinflection using linguistically enhanced sequence-to-sequence models. Our system takes an Arabic sentence and a given target gender as input and generates a gender-reinflected sentence based on the target gender. We formulate the problem as a user-aware grammatical error correction task and build an encoder-decoder architecture to jointly model reinflection for both masculine and feminine grammatical genders. We also show that adding linguistic features to our model leads to better reinflection results. The results on a blind test set using our best system show improvements over previous work, with a 3.6% absolute increase in M2 F0.5.

Tasks

Reproductions