Publication - Expanding the Language model in a low-resource hybrid MT system

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Expanding the Language model in a low-resource hybrid MT system

Research Area:  
Other topics in Computer Science
    
Type:  
In Proceedings

 

Year: 2014
Authors: George Tambouratzis
Editor: Dekai Wu, Marine Carpuat, Xavier Carreras and Eva Maria Vecchi
Book title: Proceedings of the SSST-8 Workshop (held within EMNLP-2014)
Series: Proceedings of the SSST-8 Workshop (held within EMNLP-2014)
Pages: 57-66
Address: Doha, Qatar
Organization: ACL
Date: 25-Οκτ-14
ISBN: 978-1-937284-96-1
Abstract:
The present article investigates the fusion of different language models to improve transla-tion accuracy. A hybrid MT system, recently-developed in the European Commission-funded PRESEMT project that combines ex-ample-based MT and Statistical MT princi-ples is used as a starting point. In this article, the syntactically-defined phrasal language models (NPs, VPs etc.) used by this MT sys-tem are supplemented by n-gram language models to improve translation accuracy. For specific structural patterns, n-gram statistics are consulted to determine whether the pat-tern instantiations are corroborated. Experi-ments indicate improvements in translation accuracy.
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