Word embedding and neural network on grammatical gender -- A case study of Swedish
Computation and Language
2020-07-29 v1
Abstract
We analyze the information provided by the word embeddings about the grammatical gender in Swedish. We wish that this paper may serve as one of the bridges to connect the methods of computational linguistics and general linguistics. Taking nominal classification in Swedish as a case study, we first show how the information about grammatical gender in language can be captured by word embedding models and artificial neural networks. Then, we match our results with previous linguistic hypotheses on assignment and usage of grammatical gender in Swedish and analyze the errors made by the computational model from a linguistic perspective.
Keywords
Cite
@article{arxiv.2007.14222,
title = {Word embedding and neural network on grammatical gender -- A case study of Swedish},
author = {Marc Allassonnière-Tang and Ali Basirat},
journal= {arXiv preprint arXiv:2007.14222},
year = {2020}
}
Comments
The paper was submitted to Nordic Journal of Linguistics in 2017