Enhanced Good-Turing and Cat-Cal: Two New Methods for Estimating Probabilities of English Bigrams (abbreviated version)
Kenneth Church, William A. Gale · 1989
For many pattern recognition applications including speech recognition and optical character recognition, prior models of language are used to disambiguate otherwise equally probable outputs. It is common practice to use tables of probabilities of single words, pairs of words, and triples of words (n-grams) as a prior model. Our research is directed to 'backing-off' methods, that is, methods that build an (n+l)gram model from an n-gram model.