Grammatical gender in Swedish is predictable using recurrent neural networks
This addresses a linguistic mystery in Swedish grammar, providing a computational solution for language processing tasks.
The paper tackled the problem of predicting grammatical gender for Swedish nouns, achieving high accuracy using a recurrent neural network on raw character sequences without contextual information.
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.