  Unsupervised Bilingual Dictionary Induction methods based on the
initialization and the self-learning have achieved great success in similar
language pairs, e.g., English-Spanish. But they still fail and have an accuracy
of 0% in many distant language pairs, e.g., English-Japanese. In this work, we
show that this failure results from the gap between the actual initialization
performance and the minimum initialization performance for the self-learning to
succeed. We propose Iterative Dimension Reduction to bridge this gap. Our
experiments show that this simple method does not hamper the performance of
similar language pairs and achieves an accuracy of 13.64~55.53% between English
and four distant languages, i.e., Chinese, Japanese, Vietnamese and Thai.

Computation and Language