Informace o projektu

Pattern Recognition-based Statistically Enhanced MT (PRESEMT)

Kód projektu
Období řešení
1/2010 - 12/2012
Investor / Programový rámec / typ projektu
Evropská unie
Fakulta / Pracoviště MU
Fakulta informatiky
Spolupracující organizace
Gesellschaft zurFörderung angewandter Informatik
Institute for Language and Speech Processing
Odpovědná osoba George Tambouratzis
Lexical Computing Ltd.
National Technical University of Athens
Norwegian University of Science and Technology
Logo poskytovatele

This proposal describes PRESEMT, a flexible and adaptable MT system, based on a language-independent method, whose principles ensure easy portability to new language pairs. This method attempts to overcome well-known problems of other MT approaches, e.g. bilingual corpora compilation or creation of new rules per language pair. PRESEMT will address the issue of effectively managing multilingual content and is expected to suggest a language-independent machine-learning-based methodology. The key aspects of PRESEMT involve syntactic phrase-based modelling, pattern recognition approaches (such as extended clustering or neural networks) or game theory techniques towards the development of a language-independent analysis, evolutionary algorithms for system optimisation. It is intended to be of a hybrid nature, combining linguistic processing with the positive aspects of corpus-based approaches, such as SMT and EBMT.

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