Monthly
288 pp. per issue
6 x 9, illustrated
ISSN
0899-7667
E-ISSN
1530-888X
2014 Impact factor:
2.21

Neural Computation

November 1995, Vol. 7, No. 6, Pages 1289-1303
(doi: 10.1162/neco.1995.7.6.1289)
© 1995 Massachusetts Institute of Technology
LeRec: A NN/HMM Hybrid for On-Line Handwriting Recognition
Article PDF (844.28 KB)
Abstract

We introduce a new approach for on-line recognition of handwritten words written in unconstrained mixed style. The preprocessor performs a word-level normalization by fitting a model of the word structure using the EM algorithm. Words are then coded into low resolution "annotated images" where each pixel contains information about trajectory direction and curvature. The recognizer is a convolution network that can be spatially replicated. From the network output, a hidden Markov model produces word scores. The entire system is globally trained to minimize word-level errors.