Nicolas Stroppa

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In this paper, we compare the rule­based and data­driven approaches in the context of Spanish­to­Basque Machine Translation. The rule­based system we consider has been developed specifically for Spanish­to­Basque machine translation, and is tuned to this language pair. On the contrary, the data­driven system we use is generic, and has not been specifically(More)
Basque is both a minority and a highly inflected language with free order of sentence constituents. Machine Translation of Basque is thus both a real need and a test bed for MT techniques. In this paper, we present a modular Data-Driven MT system which includes different chunkers as well as chunk aligners which can deal with the free order of sentence(More)
We present an analogical learning model which exploits the notion of formal analogi-cal proportions; this approach requires the ability to define these proportions and to implement them efficiently. We propose an algebraic definition of this notion, which applies to a large range of structured objects: words, attribute-value structures, labeled trees. We(More)
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