Weighted distance measures for efficient reduction of Gaussian mixture components in HMM-based acoustic model

摘要

In this paper, two weighted distance measures; the weighted K-L divergence and the Bayesian criterion-based distance measure are proposed to efficiently reduce the Gaussian mixture components in the HMM-based acoustic model. Conventional distance measures