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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).

Y. He, M. Chen and A. Kundu, "Alternatives to Variable Duration HMM in Handwriting Recognition," in IEEE Transactions on Pattern Analysis & Machine Intelligence, vol. 20, no. , pp. 1275-1280, 1998.
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