Word embedding and neural network on grammatical gender -- A case study of Swedish

2020/07/28 by Marc Allassonnière‐Tang, Allassonnière-Tang, Marc, Ali Basirat +1
Computer Science · #Authorship Attribution and Profiling #Computation and Language (cs.CL) #FOS: Computer and information sciences #Natural Language Processing Techniques #Topic Modeling

paper · pdf · doi:10.48550/arxiv.2007.14222

openalex publication_date 2020/07/28 · openalex created_date 2020/08/03 · openalex updated_date 2026/07/28

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.

Citations

• Functions of nominal classification

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