On-line connected handwritten word recognition by a probabilistic method

Abstract

Methods and apparatus are disclosed for recognizing handwritten words in response to an input signal from a handwriting transducer. The method includes the steps of: (a) partitioning the input signal into N frames; and (b) processing words from a vocabulary model to determine, for each processed word, a probability that the word represents a written word that is conveyed by the input signal. The determined probability is a function of N letter-frame alignment probabilities and also a probability based on a grouping of the N frames into L groups, where L is a number of letters in the word. A further step (c) identifies a word having a highest determined probability as being a most-likely word that is conveyed by the input signal. The determined probability is also a function of (a) a probability based on a frequency of occurrence of words and portions of words within a selected language model; and (b) when processing a frame other than the Nth frame, a number of frames that remain to be processed. In one embodiment of the invention all words in the vocabulary model are searched in parallel, thereby significantly reducing the recognition time. The use of a beam search technique is illustrated to perform the parallel search. Also, this invention teaches the use of hashing to increase the speed of the beam search technique.