In this paper, we report our work on incorporating syntactic and morphological information for English to Hindi statistical machine translation. Two simple and computationally inexpensive ideas have proven to be surprisingly effective: (i) reordering the English source sentence as per Hindi syntax, and (ii) using the suffixes of Hindi words. The former is done by applying simple transformation rules on the English parse tree. The latter, by using a simple suffix separation program. With only a small amount of bilingual training data and limited tools for Hindi, we achieve reasonable performance and substantial improvements over the baseline phrase-based system. Our approach eschews the use of parsing or other sophisticated linguistic tools for the target language (Hindi) making it a useful framework for statistical machine translation from English to Indian languages in general, since such tools are not widely available for Indian languages currently.
Our earlier work REF describes syntactic reordering and morphological suffix separation for English-Hindi SMT.
Simple Syntactic and Morphological Processing Can Help English-Hindi Statistical Machine Translation
Proceedings of the Third International Joint Conference on Natural Language Processing
Computer Science