Artificial bandwidth extension of spectral envelope along a Viterbi path
In this paper, we propose a hidden Markov model (HMM)-based wideband spectral envelope estimation method for the artificial bandwidth extension problem. The proposed HMM-based estimator decodes an optimal Viterbi path based on the temporal contour of the narrowband spectral envelope and then performs the minimum mean square error (MMSE) estimation of the wideband spectral envelope on this path. Experimental evaluations are performed to compare the proposed estimator to the state-of-the-art HMM and Gaussian mixture model based estimators using both objective and subjective evaluations. Objective evaluations are performed with the log-spectral distortion (LSD) and the wideband perceptual evaluation of speech quality (PESQ) metrics. Subjective evaluations are performed with the A/B pair comparison listening test. Both objective and subjective evaluations yield that the proposed wideband spectral envelope estimator consistently improves performances over the state-of-the-art estimators.
artificial bandwidth extension source-filter separation line spectral frequency joint temporal analysis