Recovery of broadband speech from narrowband speech by radial basis function neural networks

This paper presents a novel method to recovery of broadband speech from narrowband speech. The approach is based on estimating independently the spectral envelope using a radial basis function (RBF) neural network, a well-known model of artificial neural networks and the excitation function. The sim...

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Published in2002 IEEE Region 10 Conference on Computers, Communications, Control and Power Engineering. TENCOM '02. Proceedings Vol. 1; pp. 469 - 472 vol.1
Main Authors Watanabe, T., Murakami, T., Namba, M., Hoya, T., Ishida, Y.
Format Conference Proceeding
LanguageEnglish
Published IEEE 2002
Subjects
Artificial neural networks
Biological neural networks
Educational technology
Frequency estimation
Narrowband
Radial basis function networks
Signal processing
Speech processing
Telephony
Testing
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Summary:This paper presents a novel method to recovery of broadband speech from narrowband speech. The approach is based on estimating independently the spectral envelope using a radial basis function (RBF) neural network, a well-known model of artificial neural networks and the excitation function. The simulation results show that the proposed method is effective in the estimation of missing frequency components. Moreover, in listening tests, around 84% of the mean opinion score (MOS) was obtained by implementing the proposed recovery scheme.
ISBN:0780374908
9780780374904
DOI:10.1109/TENCON.2002.1181315