Audio bandwidth extension based on RBF neural network - Details

Author：

Liu, Haojie (Liu, Haojie.) | Bao, Changchun (Bao, Changchun.) (Scholars：鲍长春) | Liu, Xin (Liu, Xin.) | Zhang, Xingtao (Zhang, Xingtao.) | Zhang, Liyan (Zhang, Liyan.)

Indexed by：

EI Scopus

Abstract：

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.　©　2011　IEEE.

Keyword：

Radial basis function networks Signal processing Bandwidth Extrapolation

Author Community：

[ 1 ] [Liu, Haojie]Speech and Audio Signal Processing Laboratory, School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
[ 2 ] [Bao, Changchun]Speech and Audio Signal Processing Laboratory, School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
[ 3 ] [Liu, Xin]Speech and Audio Signal Processing Laboratory, School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
[ 4 ] [Zhang, Xingtao]Speech and Audio Signal Processing Laboratory, School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China
[ 5 ] [Zhang, Liyan]Speech and Audio Signal Processing Laboratory, School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China