Classification-Based Self-Learning for Weakly Supervised Bilingual Lexicon Induction

• DOI: 10.18653/v1/2020.acl-main.618
• Publication Date: 2020-07-29T14:14:43Z
• Authors: Mladen Karan; Ivan Vulić; Anna Korhonen; Goran Glavaš
• Keywords: 0202 electrical engineering, electronic engineering, information engineering; 02 engineering and technology; 004

Effective projection-based cross-lingual word embedding (CLWE) induction critically relies on the iterative self-learning procedure. It gradually expands the initial small seed dictionary to learn improved cross-lingual mappings. In this work, we present ClassyMap, a classification-based approach to self-learning, yielding a more robust and a more effective induction of projection-based CLWEs. Unlike prior self-learning methods, our approach allows for integration of diverse features into the iterative process. We show the benefits of ClassyMap for bilingual lexicon induction: we report consistent improvements in a weakly supervised setup (500 seed translation pairs) on a benchmark with 28 language pairs.