Spectral envelope estimation used for audio bandwidth extension based on RBF neural network

Haojie Liu, C. Bao, Xin Liu
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引用次数: 8

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.
基于RBF神经网络的频谱包络估计用于音频带宽扩展
提出了一种基于径向基函数(RBF)神经网络的频谱包络估计方法,实现了音频信号的盲带宽扩展。为了准确恢复高频分量的子带包络,利用RBF神经网络拟合低频特征与高频分量子带包络之间的关系。此外,基于非线性动力学方法重构了高频分量的精细结构,保证了扩展音频信号的稳定性。客观和主观测试结果表明,该方法优于参考方法。
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