DocumentCode :
1652612
Title :
Spectral envelope estimation used for audio bandwidth extension based on RBF neural network
Author :
Hao-jie Liu ; Chang-chun Bao ; Xin Liu
Author_Institution :
Speech & Audio Signal Process. Lab., Beijing Univ. of Technol., Beijing, China
fYear :
2013
Firstpage :
543
Lastpage :
547
Abstract :
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.
Keywords :
audio signal processing; blind source separation; radial basis function networks; signal reconstruction; spectral analysis; HF components; LF feature envelope; RBF neural network; audio signal reconstruction; blind bandwidth extension method; nonlinear dynamics; radial basis function; spectral envelope estimation method; sub-band envelope; Audio signal processing; RBF neural network; bandwidth extension; envelope estimation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
Conference_Location :
Vancouver, BC
ISSN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2013.6637706
Filename :
6637706
Link To Document :
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