Improving Bilingual Lexicon Induction with Unsupervised Post-Processing of Monolingual Word Vector Spaces

Ivan Vulić, Anna Korhonen, Goran Glavaš


Abstract
Work on projection-based induction of cross-lingual word embedding spaces (CLWEs) predominantly focuses on the improvement of the projection (i.e., mapping) mechanisms. In this work, in contrast, we show that a simple method for post-processing monolingual embedding spaces facilitates learning of the cross-lingual alignment and, in turn, substantially improves bilingual lexicon induction (BLI). The post-processing method we examine is grounded in the generalisation of first- and second-order monolingual similarities to the nth-order similarity. By post-processing monolingual spaces before the cross-lingual alignment, the method can be coupled with any projection-based method for inducing CLWE spaces. We demonstrate the effectiveness of this simple monolingual post-processing across a set of 15 typologically diverse languages (i.e., 15*14 BLI setups), and in combination with two different projection methods.
Anthology ID:
2020.repl4nlp-1.7
Volume:
Proceedings of the 5th Workshop on Representation Learning for NLP
Month:
July
Year:
2020
Address:
Online
Editors:
Spandana Gella, Johannes Welbl, Marek Rei, Fabio Petroni, Patrick Lewis, Emma Strubell, Minjoon Seo, Hannaneh Hajishirzi
Venue:
RepL4NLP
SIG:
SIGREP
Publisher:
Association for Computational Linguistics
Note:
Pages:
45–54
Language:
URL:
https://aclanthology.org/2020.repl4nlp-1.7
DOI:
10.18653/v1/2020.repl4nlp-1.7
Bibkey:
Cite (ACL):
Ivan Vulić, Anna Korhonen, and Goran Glavaš. 2020. Improving Bilingual Lexicon Induction with Unsupervised Post-Processing of Monolingual Word Vector Spaces. In Proceedings of the 5th Workshop on Representation Learning for NLP, pages 45–54, Online. Association for Computational Linguistics.
Cite (Informal):
Improving Bilingual Lexicon Induction with Unsupervised Post-Processing of Monolingual Word Vector Spaces (Vulić et al., RepL4NLP 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.repl4nlp-1.7.pdf
Video:
 http://slideslive.com/38929773