Nonlinear bandwidth extension of audio signals based on hidden Markov model

Abstract

A nonlinear audio bandwidth extension method based on hidden Markov model (HMM) is proposed to reconstruct super wideband audio signals from wideband audio signals. The sub-band energy of high frequencies is estimated based on HMM according to the low-frequency features of audio signals. The smoothness of energy transition for the extended audio signals can be improved in time domain and frequency domain. In addition, the fine information of high-frequency components is recovered to guarantee the timbre of the extended audio by nonlinear prediction based on the nearest-neighbor matching. The objective and subjective test results indicate that the proposed method outperforms the conventional methods including blind bandwidth extension and nonlinear extensions.