A statistical approach to machine translation
Computational Linguistics
A systematic comparison of various statistical alignment models
Computational Linguistics
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
Using POS information for statistical machine translation into morphologically rich languages
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 1
BLEU: a method for automatic evaluation of machine translation
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Statistical phrase-based translation
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Feature-rich part-of-speech tagging with a cyclic dependency network
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Moses: open source toolkit for statistical machine translation
ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
Mining complex predicates in Hindi using a parallel Hindi-English corpus
MWE '09 Proceedings of the Workshop on Multiword Expressions: Identification, Interpretation, Disambiguation and Applications
Stepwise mining of multi-word expressions in Hindi
MWE '11 Proceedings of the Workshop on Multiword Expressions: from Parsing and Generation to the Real World
Comparative study on corpora for speech translation
IEEE Transactions on Audio, Speech, and Language Processing
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Verb plays a crucial role of specifying the action or function performed in a sentence. In translating English to morphologically richer language like Hindi, the organization and the order of verbal constructs contributes to the fluency of the language. Mere statistical methods of machine translation are not sufficient enough to consider this aspect. Identification of verb parts in a sentence is essential for its understanding and they constitute as if they are a single entity. Considering them as a single entity improves the translation of the verbal construct and thus the overall quality of the translation. The paper describes a strategy for pre-processing and for identification of verb parts in source and target language corpora. The steps taken towards reducing sparsity further helped in improving the translation results.