Advanced signal processing in speech communication

In digital mobile communications several measures are taken beyond speech coding to enhance the perceived quality in the presence of acoustic background noise and transmission errors. In premium mobile phones meanwhile advanced algorithms for noise suppression, error concealment, and finally artificial bandwidth extension come to practical application. It will be shown in this contribution that theses three different concepts of speech enhancement are actually based on the same common principle of conditional estimation, taking statistical a priori knowledge into account. Recent developments in these three areas are presented.

[1]  Rainer Martin,et al.  SPEECH ENHANCEMENT IN THE DFT DOMAIN USING LAPLACIAN SPEECH PRIORS , 2003 .

[2]  Norbert Wiener,et al.  Extrapolation, Interpolation, and Smoothing of Stationary Time Series , 1964 .

[3]  Van Trees,et al.  Detection, Estimation, and Modulation Theory. Part 1 - Detection, Estimation, and Linear Modulation Theory. , 1968 .

[4]  Robert M. Gray,et al.  An Algorithm for Vector Quantizer Design , 1980, IEEE Trans. Commun..

[5]  Norbert Wiener,et al.  Extrapolation, Interpolation, and Smoothing of Stationary Time Series, with Engineering Applications , 1949 .

[6]  Saeed Vaseghi,et al.  Advanced Signal Processing and Digital Noise Reduction , 1996 .

[7]  Roch Lefebvre,et al.  The adaptive multirate wideband speech codec (AMR-WB) , 2002, IEEE Trans. Speech Audio Process..

[8]  Douglas A. Reynolds,et al.  Robust text-independent speaker identification using Gaussian mixture speaker models , 1995, IEEE Trans. Speech Audio Process..

[9]  Peter Vary,et al.  Noise reduction by joint maximum a posteriori spectral amplitude and phase estimation with super-Gaussian speech modelling , 2004, 2004 12th European Signal Processing Conference.

[10]  David Malah,et al.  Speech enhancement using a minimum mean-square error log-spectral amplitude estimator , 1984, IEEE Trans. Acoust. Speech Signal Process..

[11]  Peter Vary,et al.  Softbit speech decoding: a new approach to error concealment , 2001, IEEE Trans. Speech Audio Process..

[12]  Rainer Martin,et al.  Speech enhancement using MMSE short time spectral estimation with gamma distributed speech priors , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[13]  H. V. Trees Detection, Estimation, And Modulation Theory , 2001 .

[14]  T. Lotter NOISE REDUCTION BY MAXIMUM A POSTERIORI SPECTRAL AMPLITUDE ESTIMATION WITH SUPERGAUSSIAN SPEECH MODELING , 2003 .

[15]  Ulrich Kornagel Spectral widening of the excitation signal for telephone-band speech enhancement , 2001 .

[16]  Peter Jax,et al.  On artificial bandwidth extension of telephone speech , 2003, Signal Process..

[17]  Simon J. Godsill,et al.  Efficient Alternatives to the Ephraim and Malah Suppression Rule for Audio Signal Enhancement , 2003, EURASIP J. Adv. Signal Process..

[18]  Rainer Martin,et al.  Noise power spectral density estimation based on optimal smoothing and minimum statistics , 2001, IEEE Trans. Speech Audio Process..

[19]  J. L. Melsa,et al.  Decision and Estimation Theory , 1981, IEEE Transactions on Systems, Man, and Cybernetics.

[20]  Peter J. Patrick Enhancement of band-limited speech signals , 1983 .