Multilingual Factor Analysis
Machine Learning
2019-10-25 v2 Computation and Language
Machine Learning
Abstract
In this work we approach the task of learning multilingual word representations in an offline manner by fitting a generative latent variable model to a multilingual dictionary. We model equivalent words in different languages as different views of the same word generated by a common latent variable representing their latent lexical meaning. We explore the task of alignment by querying the fitted model for multilingual embeddings achieving competitive results across a variety of tasks. The proposed model is robust to noise in the embedding space making it a suitable method for distributed representations learned from noisy corpora.
Cite
@article{arxiv.1905.05547,
title = {Multilingual Factor Analysis},
author = {Francisco Vargas and Kamen Brestnichki and Alex Papadopoulos-Korfiatis and Nils Hammerla},
journal= {arXiv preprint arXiv:1905.05547},
year = {2019}
}
Comments
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics