30. A method as set forth in claim 28 wherein the determined probability is also a function of a probability based on a frequency of occurrence of words, and portions of words, within a selected language model.
28. A method for recognizing handwritten words in response to an input signal from a handwriting transducer, comprising the steps of: partitioning the input signal into N frames; operating a data processor to determine for each of the N frames a probability that the portion of the input signal contained therein is a portion of a letter belonging to a predetermined letter set; accessing a vocabulary model with the data processor to retrieve a word therefrom; processing the retrieved word to determine a probability that the word represents a written word that is conveyed by the input signal, the determined probability being a function of N letter-frame alignment probabilities and also being a function of a probability based on a grouping of the N frames into L groups, where L is a number of letters in the word being processed; and identifying a word having a highest determined probability as being a most-likely word that is conveyed by the input signal.