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In this paper, we present a novel approach to integrate speech recognition and rule-based machine translation by lattice parsing. The presented approach is hybrid in two senses. First, it combines structural and statistical methods for language modeling task. Second, it employs a chart parser which utilizes manually created syntax rules in addition to(More)
In this paper, we present a powerful Arabic morphological analyzer and generator. The approach employs finite state machines enriched with unification capability. The presented system is used as a component in both statistical and rule based machine translation systems. We give detailed illustrations on how we handle nominal and verbal morphology in Arabic.(More)
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