DirecTL: a Language Independent Approach to Transliteration

Abstract

We present DirecTL: an online discriminative sequence prediction model that employs a many-to-many alignment between target and source. Our system incorporates input segmentation, target character prediction, and sequence modeling in a unified dynamic programming framework. Experimental results suggest that DirecTL is able to independently discover many of the language-specific regularities in the training data.