Audio bandwidth extension based on RBF neural network

In this paper a new method of blind bandwidth extension from wideband (WB) to super-wideband (SWB) audio is proposed. The Radial Basic Function (RBF) neural network is utilized to predict the coefficients of high-frequency (HF) based on the nonlinear characteristics of audio spectrum series. In addition, the linear extrapolation is used for reconstructing the envelop of HF spectrum. The bandwidth of the reconstructed audio signals is extended to SWB by using the proposed method. The result of the objective performance evaluation indicates that the proposed method can reconstruct the truncated HF components effectively and outperforms the conventional algorithms of blind bandwidth extension.