Learning Multilingual Word Embeddings in Latent Metric Space: A Geometric Approach
Learning Multilingual Word Embeddings in Latent Metric Space: A Geometric Approach
Abstract We propose a novel geometric approach for learning bilingual mappings given monolingual embeddings and a bilingual dictionary. Our approach decouples the source-to-target language transformation into (a) language-specific rotations on the original embeddings to align them in a common, latent space, and (b) a language-independent similarity metric in this common …