Q. Gong, B. Champagne, and P. Kabal
"Noise Power Spectral Density Matrix Estimation Based on Modified IMCRA", Proc. Asilomar Conf. Signals, Systems & Computers (Pacific Grove, CA), pp. 1389-1395, Nov. 2014.
In this paper, we present a new method for noise power spectral density (PSD) matrix estimation based on IMCRA which consists of two parts. For the auto-PSD (diagonal) estimation, we propose a modification to IMCRA where a special level detector is employed to improve the tracking of non-stationary noise backgrounds. For the cross-PSD (off-diagonal) estimation, we propose to calculate a smoothed cross-periodogram by using estimated noise components derived as residuals after the application of a speech enhancement algorithm on the individual microphone signals. Simulation results show the effectiveness of our proposed approach in estimating the noise PSD matrix and its robustness against reverberation when used in combination with an MVDR-based speech enhancement system.
M. Movassagh and P. Kabal
"New Bit-Plane Probability Calculations for Scalable to Lossless Audio Coding", Proc. IEEE Int. Conf. Acoustics, Speech, Signal Processing (Florence, Italy), pp. 3675-3679, May 2014.
Considering the properties of the residual signal, core-based bit-plane probabilities are provided for MPEG-4 Audio Scalable to Lossless Coding (SLS), which matches the quantization and coding performed in the core layer. Using the same strategy, new probabilities are obtained to consider the clipping effect in bit-plane coding of an unbounded signal, which is useful for non-core mode of SLS coding. Simulations show that considering the core layer parameters and the clipping effect improve the bit-plane probabilities estimation compared to the existing method.