Rishabh Srivastava


2014

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Hindi to English Machine Translation: Using Effective Selection in Multi-Model SMT
Kunal Sachdeva | Rishabh Srivastava | Sambhav Jain | Dipti Sharma
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)

Recent studies in machine translation support the fact that multi-model systems perform better than the individual models. In this paper, we describe a Hindi to English statistical machine translation system and improve over the baseline using multiple translation models. We have considered phrase based as well as hierarchical models and enhanced over both these baselines using a regression model. The system is trained over textual as well as syntactic features extracted from source and target of the aforementioned translations. Our system shows significant improvement over the baseline systems for both automatic as well as human evaluations. The proposed methodology is quite generic and easily be extended to other language pairs as well.

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Creating a PurposeNet Ontology: An insight into the issues encountered during ontology creation
Rishabh Srivastava | Soma Paul
Proceedings of the 11th International Conference on Natural Language Processing

2013

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Transliteration Systems across Indian Languages Using Parallel Corpora
Rishabh Srivastava | Riyaz Ahmad Bhat
Proceedings of the 27th Pacific Asia Conference on Language, Information, and Computation (PACLIC 27)