Integration of two stochastic context-free grammars

Some problems in speech and natural language processing involve combining two information sources each modeled by a stochastic context-free grammar. Such cases include parsing the output of a speech recognizer by using a contextfree language model, finding the best solution among all the possible ones in language generation, preserving ambiguity in machine translation. In these cases usually at least one of the two grammars is non-recursive. In order to find the best solution while taking into account both grammars, the two probabilities must be integrated. One of the most important advantages of using a non-recursive context-free model is its compactness. Therefore, it is important to exploit this property when searching for the solution. In this paper, an algorithm aiming to this goal is presented, based on a recent work [1] in which the non probabilistic case is considered.