Audio Bandwidth Extension Method Using Similarity Correlation Degree-Based Neural Network
Xi Liu · Dianzi xuebao · 2015
The bandwidth limitation of wideband audio degrades the subjective quality and the naturalness. In this paper,a bandwidth extension of audio signals from wideband to super-wideband was proposed by using a similarity correlation degree-based neural network.Firstly,the fine spectrum of wideband audio was converted to a multi-dimensional phase space. Then,a similarity correlation degree-based neural network was built up to reproduce the high-frequency fine spectrum. In addition,Gaussian mixture model was used to estimate the high-frequency spectral envelope. Finally,the bandwidth was extended to super-wideband by the proposed method in the ITU-T G. 722. 1wideband codec. Evaluation results indicate that the proposed method is preferred over the reference methods and achieves a comparable subjective quality with the G. 722. 1C super-wideband codec.