Normalized Word Embedding and Orthogonal Transform for Bilingual Word Translation
Xing Chao, Dong Wang, Chao Liu, Yiye Lin · 2015
Word embedding has been found to be highly powerful to translate words from one language to another by a simple linear transform.However, we found some inconsistence among the objective functions of the embedding and the transform learning, as well as the distance measurement.This paper proposes a solution which normalizes the word vectors on a hypersphere and constrains the linear transform as an orthogonal transform.The experimental results confirmed that the proposed solution can offer better performance on a word similarity task and an English-to-Spanish word translation task.