Skip to Main Content
The modified Viterbi algorithm is a powerful, and increasingly used, tool for using contextual information in text recognition in its various forms. As yet, no known studies have been published concerning its robustness with respect to source statistics. This paper describes experiments performed to determine the sensitivity of the algorithm to variations in source statistics. The results of the experiments show that a character-recognition machine incorporating the modified Viterbi algorithm, using N-gram statistics estimated from source A does not deteriorate in performance when operating on a passage from source B even if A and B differ significantly in N-gram distributions or entropy.