Classification-Based Self-Learning for Weakly Supervised Bilingual Lexicon Induction
Mladen Karan, Ivan Vulić, Anna Korhonen, Goran Glavaš · 2020
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.