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    <name type="personal">
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    <abstract>Most methods to learn bilingual word embeddings rely on large parallel corpora, which is difficult to obtain for most language pairs. This has motivated an active research line to relax this requirement, with methods that use document-aligned corpora or bilingual dictionaries of a few thousand words instead. In this work, we further reduce the need of bilingual resources using a very simple self-learning approach that can be combined with any dictionary-based mapping technique. Our method exploits the structural similarity of embedding spaces, and works with as little bilingual evidence as a 25 word dictionary or even an automatically generated list of numerals, obtaining results comparable to those of systems that use richer resources.</abstract>
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%0 Conference Proceedings
%T Learning bilingual word embeddings with (almost) no bilingual data
%A Artetxe, Mikel
%A Labaka, Gorka
%A Agirre, Eneko
%Y Barzilay, Regina
%Y Kan, Min-Yen
%S Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2017
%8 July
%I Association for Computational Linguistics
%C Vancouver, Canada
%F artetxe-etal-2017-learning
%X Most methods to learn bilingual word embeddings rely on large parallel corpora, which is difficult to obtain for most language pairs. This has motivated an active research line to relax this requirement, with methods that use document-aligned corpora or bilingual dictionaries of a few thousand words instead. In this work, we further reduce the need of bilingual resources using a very simple self-learning approach that can be combined with any dictionary-based mapping technique. Our method exploits the structural similarity of embedding spaces, and works with as little bilingual evidence as a 25 word dictionary or even an automatically generated list of numerals, obtaining results comparable to those of systems that use richer resources.
%R 10.18653/v1/P17-1042
%U https://aclanthology.org/P17-1042
%U https://doi.org/10.18653/v1/P17-1042
%P 451-462

Markdown (Informal)

[Learning bilingual word embeddings with (almost) no bilingual data](https://aclanthology.org/P17-1042) (Artetxe et al., ACL 2017)

• Learning bilingual word embeddings with (almost) no bilingual data (Artetxe et al., ACL 2017)

ACL

• Mikel Artetxe, Gorka Labaka, and Eneko Agirre. 2017. Learning bilingual word embeddings with (almost) no bilingual data. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 451–462, Vancouver, Canada. Association for Computational Linguistics.