HMM-based frequency bandwidth extension for speech enhancement using line spectral frequencies

Abstract

A new hidden Markov model (HMM) based frequency bandwidth extension algorithm using line spectral frequencies (HMM-LSF-FBE) is proposed. The proposed algorithm improves the performance of the traditional LSF-based extension algorithm by exploiting an HMM to indicate the proper representatives of different speech frames, and by applying a minimum mean square criterion to estimate the high-band LSF values. The proposed algorithm has been tested and compared to the traditional LSF-based algorithm in terms of the perceptual evaluation of speech quality (PESQ) objective measure and speech spectrograms. Simulation results show that the proposed algorithm outperforms the traditional method by eliminating undesired whistling sounds completely. In addition, the bandwidth extended speech signals created by the proposed algorithm are significantly more pleasant to the human ear than the original narrowband speech signals from which they are derived.