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Grammatical gender in Swedish is predictable using recurrent neural networks

Authors :
Zec, Edvin Listo
Mogren, Olof
Publication Year :
2023

Abstract

The grammatical gender of Swedish nouns is a mystery. While there are few rules that can indicate the gender with some certainty, it does in general not depend on either meaning or the structure of the word. In this paper we demonstrate the surprising fact that grammatical gender for Swedish nouns can be predicted with high accuracy using a recurrent neural network (RNN) working on the raw character sequence of the word, without using any contextual information.

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2306.10869
Document Type :
Working Paper