Supervised Alignment of Word Embeddings

This code aligns word embeddings from two languages with a bilingual lexicon. The details of our approach can be found in [1].

The code is in Python 3 and requires NumPy.

The script example.sh shows how to use this code to learn and evaluate a bilingual alignment of word embeddings.

The word embeddings used in [1] can be found on the fastText project page and the supervised bilingual lexicons on the MUSE project page.

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Wikipedia fastText embeddings aligned with our method can be found here.

References

If you use this code, please cite:

[1] A. Joulin, P. Bojanowski, T. Mikolov, H. Jegou, E. Grave, Loss in Translation: Learning Bilingual Word Mapping with a Retrieval Criterion

@InProceedings{joulin2018loss,
    title={Loss in Translation: Learning Bilingual Word Mapping with a Retrieval Criterion},
    author={Joulin, Armand and Bojanowski, Piotr and Mikolov, Tomas and J\'egou, Herv\'e and Grave, Edouard},
    year={2018},
    booktitle={Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing},
}