An Aided Adaptive Character Reader for Machine Translation of Languages

摘要

An elementary procedure for the synthesis of a character recognition device based upon a learning experiment is described. Utilizing information derived from a significant sample of the set of characters to be read and given identification of the samples by a human operator, a computer defines a set of 'filters.' These filters may then be used to transform unknown characters having similar type characteristics. During the recognition process a probability matrix for each character in the alphabet is used to compute a figure of merit for the hypothesis that an unknown character is the same as a known character. It is shown that this elementary model might adequately serve for construction of a fast input device for a language translation machine if it were able to make use of frequency distribution characteristics of the dictionary. A possible implementation with a raw character reading rate of up to 500 characters a second appears feasible. (Author)