A Tightly-coupled Unsupervised Clustering and Bilingual Alignment Model for Transliteration

Improving Bilingual Lexicon Induction with Unsupervised Post-Processing of Monolingual Word Vector Spaces

Work on projection-based induction of cross-lingual word embedding spaces (CLWEs) predominantly focuses on the improvement of the projection (i.e., mapping) mechanisms. In this work, in contrast, we show that a simple me…

Unsupervised Word Mapping Using Structural Similarities in Monolingual Embeddings

Most existing methods for automatic bilingual dictionary induction rely on prior alignments between the source and target languages, such as parallel corpora or seed dictionaries. For many language pairs, such supervised…

Bilingual alignment transfers to multilingual alignment for unsupervised parallel text mining

This work presents methods for learning cross-lingual sentence representations using paired or unpaired bilingual texts. We hypothesize that the cross-lingual alignment strategy is transferable, and therefore a model tra…

Word Clustering Approach to Bilingual Document Alignment (WMT 2016 Shared Task)

On the Limitations of Unsupervised Bilingual Dictionary Induction

Unsupervised machine translation---i.e., not assuming any cross-lingual supervision signal, whether a dictionary, translations, or comparable corpora---seems impossible, but nevertheless, Lample et al. (2018) recently pr…