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    <abstract>Most recent approaches to bilingual dictionary induction find a linear alignment between the word vector spaces of two languages. We show that projecting the two languages onto a third, latent space, rather than directly onto each other, while equivalent in terms of expressivity, makes it easier to learn approximate alignments. Our modified approach also allows for supporting languages to be included in the alignment process, to obtain an even better performance in low resource settings.</abstract>
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%0 Conference Proceedings
%T Generalizing Procrustes Analysis for Better Bilingual Dictionary Induction
%A Kementchedjhieva, Yova
%A Ruder, Sebastian
%A Cotterell, Ryan
%A Søgaard, Anders
%Y Korhonen, Anna
%Y Titov, Ivan
%S Proceedings of the 22nd Conference on Computational Natural Language Learning
%D 2018
%8 October
%I Association for Computational Linguistics
%C Brussels, Belgium
%F kementchedjhieva-etal-2018-generalizing
%X Most recent approaches to bilingual dictionary induction find a linear alignment between the word vector spaces of two languages. We show that projecting the two languages onto a third, latent space, rather than directly onto each other, while equivalent in terms of expressivity, makes it easier to learn approximate alignments. Our modified approach also allows for supporting languages to be included in the alignment process, to obtain an even better performance in low resource settings.
%R 10.18653/v1/K18-1021
%U https://aclanthology.org/K18-1021
%U https://doi.org/10.18653/v1/K18-1021
%P 211-220

Markdown (Informal)

[Generalizing Procrustes Analysis for Better Bilingual Dictionary Induction](https://aclanthology.org/K18-1021) (Kementchedjhieva et al., CoNLL 2018)

• Generalizing Procrustes Analysis for Better Bilingual Dictionary Induction (Kementchedjhieva et al., CoNLL 2018)

ACL

• Yova Kementchedjhieva, Sebastian Ruder, Ryan Cotterell, and Anders Søgaard. 2018. Generalizing Procrustes Analysis for Better Bilingual Dictionary Induction. In Proceedings of the 22nd Conference on Computational Natural Language Learning, pages 211–220, Brussels, Belgium. Association for Computational Linguistics.