• 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