Cursive script recognition using semi continuous hidden Markov models in combination with simple features

An approach is presented to use left-to-right Hidden Markov Models adopted from speech recognition for recognition of cursive script. A sequence of feature vectors is obtained from the script line deliberately doing without preprocessing to reduce writer variability. The goal is to investigate wether or not it is possible to statistically model cursive script with HMMs for recognition based on such features