Paper
Word normalization for on-line handwritten word recognition
We introduce a new approach to normalizing words written with an electronic stylus that applies to all styles of handwriting (upper case, lower case, printed, cursive, or mixed). A geometrical model of the word spatial structure is fitted to the pen trajectory using the EM algorithm. The fitting process maximizes the likelihood of the trajectory given the model and a set a priors on its parameters. The method was evaluated and integrated to a recognition system that combines neural networks and hidden Markov models. 1 Introduction Natural handwriting can be a mixture of different "styles", lower case printed, upper case, cursive, and punctuation. In order to improve the success of penbased computers, we would like a recognizer that reliably handles such handwriting, but its implementation faces major technical challenges [9]. It has been long known that, although characters taken in isolation can be very ambiguous, considerable information is available from the context of the whole wo...
Authors: Yoshua Bengio · Yann LeCun