PRESEMT

Evaluating the translation accuracy of a novel language-independent MT methodology

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Research areas: Year: 2012
Type of Publication: In Proceedings Keywords: hybrid machine translation; language-independent methodology; MT evaluation
Authors:
  • 34, 46
Book title: Proceedings of the 24th International Conference on Computational Linguistics
Address: Mumbai, India
Organization: COLING2012 Month: December 8-15
Abstract:
The current paper evaluates the performance of the PRESEMT methodology, which facilitates the creation of machine translation (MT) systems for different language pairs. This methodology aims to develop a hybrid MT system that extracts translation information from large, predominantly monolingual corpora, using pattern recognition techniques. PRESEMT has been designed to have the lowest possible requirements on specialised resources and tools, given that for many languages (especially less widely used ones) only limited linguistic resources are available. In PRESEMT, the main translation process is divided into two phases, the first determining the overall structure of a target language (TL) sentence, and the second disambiguating between alternative translations for words or phrases and establishing local word order. This paper describes the latest version of the system and evaluates its translation accuracy, while also benchmarking the PRESEMT performance by comparing it with other established MT systems using objective measures.
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The research leading to these results has received funding from the European Community's
Seventh Framework Programme (FP7/2007-2013) under grant agreement No 248307.