Babylonpartners/fastText_multilingual

However these vectors are monolingual; meaning that while similar words within a language share similar vectors, translation words from different languages do not have similar vectors. In a recent paper at ICLR 2017, we showed how the SVD can be used to learn a linear transformation (a matrix), which aligns monolingual vectors from two languages in a single vector space. In this repository we provide 78 matrices, which can be used to align the majority of the fastText languages in a single space. This readme explains how the matrices should be used. We also present a simple evaluation task, where we show we are able to successfully predict the translations of words in multiple languages.