We extend stochastic context-free grammars such that the probability of applying a production can depend on the length of the subword that is generated from the application and sho...
Abstract. This paper explores the use of initial Stochastic Context-Free Grammars (SCFG) obtained from a treebank corpus for the learning of SCFG by means of estimation algorithms....
We argue that some of the computational complexity associated with estimation of stochastic attributevalue grammars can be reduced by training upon an informative subset of the fu...
Stochastic context-free grammars (SCFGs) have long been recognized as useful for a large variety of tasks including natural language processing, morphological parsing, speech reco...
We introduce and study Recursive Markov Chains (RMCs), which extend ordinary finite state Markov chains with the ability to invoke other Markov chains in a potentially recursive m...