Using Multilingual Topic Models for Improved Alignment in English-Hindi MT

Parallel corpora are often injected with bilingual dictionaries for improved Indian language machine translation (MT). In absence of such dictionaries, a coarse dictionary may be required. This paper demonstrates the use of a multilingual topic model for creating coarse dictionaries for English-Hindi MT. We compare our approaches with: (a) a baseline with no additional dictionary injection, and (b) a corpus with a good quality dictionary. Our results show that the existing Cartesian product approach which is used to create the pseudo-parallel data results in a degradation on tourism and health datasets, for English-Hindi MT. Our paper points to the fact that existing Cartesian approach using multilingual topics (devised for European languages) may be detrimental for Indian