This paper proposes a sequential coupling of a Hidden Markov Model (HMM) recognizer for offline handwritten English sentences with a probabilistic bottom-up chart parser using Sto...
: Stochastic Context-Free Grammars (SCFG) has been shown to be effective in modelling RNA secondary structure for searches. Our previous work (Cai et al., 2003) in Stochastic Paral...
Yinglei Song, Chunmei Liu, Russell L. Malmberg, Co...
We report grammar inference experiments on partially parsed sentences taken from the Wall Street Journal corpus using the inside-outside algorithm for stochastic context-free gram...
We present an algorithm for computing n-gram probabilities from stochastic context-free grammars, a procedure that can alleviate some of the standard problems associated with n-gr...
We present a bottom-up parsing algorithm for stochastic context-free grammars that is able (1) to deal with multiple interpretations of sentences containing compoundwords; (2) to ...
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 describe a framework for inducing probabilistic grammars from corpora of positive samples. First, samples are incorporated by adding ad-hoc rules to a working grammar; subseque...
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 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...
Monotone systems of polynomial equations (MSPEs) are systems of fixed-point equations X1 = f1(X1, . . . , Xn), . . . , Xn = fn(X1, . . . , Xn) where each fi is a polynomial with p...
Stefan Kiefer, Michael Luttenberger, Javier Esparz...