A new HMM training and testing scheme

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A new HMM training and testing scheme

Ko, Albert Hung Ren and Sabourin, Robert and De Souza Britto, Alceu

Proceedings – International Conference on Pattern Recognition 2008

Abstract : One of disadvantages of Hidden Markov Models (HMMs) is its low resistance to unexpected noises among observation sequences. Unexpected noises in a sequence usually “break” a sequence of observations, and then makes this sequence unrecognizable for trained models. We propose a new HMM training and testing scheme, which compensates some of the negative effects of such noises. We carried out experiment on handwritten digit recognition problem and the result suggests our proposal can be as effective as multiclassifier systems. © 2008 IEEE.

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