Nokia Corporation

Sarmad Malik

Ville Mikael Myllyla

Jukka Vartiainen

Jari Petteri Sjoberg

Gerald Enzner

Both a cascade and a multichannel joint Bayesian estimator are provided for suppressing acoustic echo. An expansion basis (Power/Fourier series) is selected to convert a sample-based input signal xinto a DFT-domain multichannel signal [X, . . . X]. The posterior of unknown states (e.g., mean &#x174;and covariance Pof the echo path Wand the mean &#xe2;and covariance Qof the nonlinear coefficients a; or channel-wise mean &#x174;and multichannel covarianceof a compound quantity formed by merging together the echo path Wand the inonlinear coefficient a) and model parameters &#x3b8;are estimated; and Kalman gain factor(s) Kare computed for optimal adaptation of the posterior of unknown states. An echo signal &#x176;is estimated using the multichannel input signal [X, . . . X] and the adapted posterior; and an error signal Eis generated. Residual echo is suppressed by post-filtering the error signal Ewith a weighting function &#x3c8;which depends on the adapted posterior, and the filtered error signal &#x15d;'is then transmitted to a far-end.

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Bochum, Germany

Sarmad Malik