DFKI-LT - How can shallow NLP help a machine translation system

Petr Homola, Jakub Piskorski
How can shallow NLP help a machine translation system
1 Proceedings of the Conference Human Language Technologies - The Baltic Perspective, April 2004, Riga, Latvia, 2004
 
The historical EU enlargement will have an enormous impact on all European countries. In particular, due to the wide variety of languages spoken in the extended EU, machine translation (MT) poses a challenging and intriguing task. Six from the �new� EU languages belong to the Balto-Slavonic language family. This paper focuses on MT among these languages, which can be achieved by relatively simple means. We present an experimental MT system for related languages (currently Baltic and Slavonic) and explain how its complexity can be reduced by exploiting similarities between the source and target language.
 
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