Two dissimilarity measures for HMMs and their application in phoneme model clustering
This paper introduces two approximations of the Kullback-Leibler divergence for hidden Markov models (HMMs). The first one is a generalization of an approximation originally presented for HMMs with discrete observation densities. In that case, the HMMs are assumed to be ergodic and the topologies si...
| Main Authors: | , , , , |
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| Format: | Conference item |
| Published: |
2002
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