Generalizing and Improving Bilingual Word Embedding Mappings with a Multi-Step Framework of Linear Transformations

@inproceedings{Artetxe2018GeneralizingAI,
  title={Generalizing and Improving Bilingual Word Embedding Mappings with a Multi-Step Framework of Linear Transformations},
  author={Mikel Artetxe and Gorka Labaka and Eneko Agirre},
  booktitle={AAAI},
  year={2018}
}
Using a dictionary to map independently trained word embeddings to a shared space has shown to be an effective approach to learn bilingual word embeddings. In this work, we propose a multi-step framework of linear transformations that generalizes a substantial body of previous work. The core step of the framework is an orthogonal transformation, and existing methods can be explained in terms of the additional normalization, whitening, re-weighting, de-whitening and dimensionality reduction… CONTINUE READING