Application of the variance compensation likelihood measure for robust hidden Markov model in noise

摘要

This letter presents covariance matrix adaptation based upon the incorporation of the projection-based group delay scheme (PGDS) with a semi-continuous hidden Markov model (HMM) for the minimization of undesirable effects in noisy environments. The proposed approach fits the covariance matrix using a variance adaptive function to balance the mismatch between different environments.