For centuries, scholars have explored the deep links among human languages. In this paper, we present a class of probabilistic models that use these links as a form of naturally o...
This paper investigates the application of a probabilistic parser for natural language on the list of the Nbest sentences produced by an off-line recognition system for cursive h...
We present a novel disambiguation method for unification-based grammars (UBGs). In contrast to other methods, our approach obviates the need for probability models on the UBG side...
Integer Linear Programming has recently been used for decoding in a number of probabilistic models in order to enforce global constraints. However, in certain applications, such a...
Common wisdom has it that tile bias of stochastic grammars in favor of shorter deriwttions of a sentence is hamfful and should be redressed. We show that the common wisdom is wron...