This paper presents English-Hindi transliteration in the NEWS 2009 Machine Transliteration Shared Task adding source context modeling into state-of-the-art log-linear phrase-based statistical machine translation (PB-SMT). Source context features enable us to exploit source similarity in addition to target similarity, as modelled by the language model. We use a memory-based classification framework that enables efficient estimation of these features while avoiding data sparseness problems.We carried out experiments both at character and transliteration unit (TU) level. Position-dependent source context features produce significant improvements in terms of all evaluation metrics.
al REF have developed English to Hindi Transliteration system based on the phrase-based statistical method (PB-SMT).
English-Hindi Transliteration Using Context-Informed PB-SMT: the DCU System for NEWS 2009
Proceedings of the 2009 Named Entities Workshop: Shared Task on Transliteration (NEWS 2009)
Computer Science