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<p><b>Abstract</b>—A successful handwritten word recognition (HWR) system using Variable Duration Hidden Markov Model (VDHMM) and the PD-HMM strategy is easy to implement. The central theme of this paper is to show that if the duration statistics are computed, it could be utilized to implement an MD-HMM approach for better experimental results. This paper also describes a PD-HMM based HWR system where the duration statistics are not explicitly computed, but results are still comparable to VDHMM based HWR scheme [<ref rid="bibi12751" type="bib">1</ref>].</p>
Variable duration HMM (VDHMM), path discriminant HMM (PD-HMM), model discriminant HMM (MD-HMM), nonergodic HMM (NEHMM), variable sequence length HMM (VSLHMM), adaptive length Viterbi algorithm (ALVA).
Yang He, Mou-Yen Chen, Amlan Kundu, "Alternatives to Variable Duration HMM in Handwriting Recognition", IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 20, no. , pp. 1275-1280, November 1998, doi:10.1109/34.730561
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