The bandwidth limitation of wideband audio systems degrades the subjective quality and naturalness of audio signals. In this paper, a new method for blind bandwidth extension of wideband audio signals is proposed based on ensemble echo state network with temporal evolution. The high-frequency components in the band of 7 ~14 kHz are artificially restored only from the information in the wideband audio. For each region in the wideband feature space, a specific echo state network with recurrent structure is explored to dynamically model the local mapping relationship between wideband audio features and high-frequency spectral envelope. The transition process among regions is modeled by a hidden Markov model, and a network ensemble technique based on temporal evolution is used to fuse multiple echo state networks such that the high-frequency spectral envelope is estimated. Combining the high-frequency fine spectrum extended by spectral translation, the proposed method can effectively extend the wideband audio to super wideband. In addition, the proposed extension method is applied to the ITU-T G.729.1 wideband audio codec and is further evaluated in comparison with the ITU-T G.729.1 Annex E super-wideband audio codec and the hidden Markov model-based reference bandwidth extension method. Objective quality evaluation results indicate that the proposed method is preferred over the hidden Markov model-based reference bandwidth extension method in terms of log spectral distortion, cosh measure, and differential log spectral distortion. Further, the proposed method improves the auditory quality of the wideband audio and also gains a good performance in the subjective listening tests.

In this paper a new spectral envelope estimation method based on radial basis function (RBF) neural network is proposed for implementing a blind bandwidth extension method of audio signals. To make the sub-band envelope of high-frequency (HF) components accurately recovered, the RBF neural network is utilized to fit the relationship between low-frequency (LF) features and sub-band envelope of HF components. In addition, the fine structure of HF components which can guarantee the timber of the extended audio signal is reconstructed based on nonlinear dynamics. The objective and subjective test results indicate that the proposed method outperforms the reference methods.

The quality of audio signals that have been encoded with low-bit rate audio coding standards is degraded because the high frequency information has been removed. The quality of such audio signals can, however, be improved by reconstructing the high frequency information which was lost. In this paper the principles of audio signal production and the characteristics of the human hearing system have been used to develop a blind high frequency reconstruction method based on chaotic prediction theory. Performance evaluation with objective and subjective tests has shown that this method is, in most cases, more efficient than other blind high frequency reconstruction methods.