PSD Estimation of Multiple Sound Sources in a Reverberant Room Using a Spherical Microphone Array
This work addresses source separation and PSD estimation in acoustics, particularly for multi-source reverberant settings, representing an incremental improvement over existing beamformer-based techniques.
The paper tackles the problem of estimating power spectral densities (PSDs) for multiple sound sources in reverberant environments using a spherical microphone array, achieving improved performance in handling more sources than conventional methods through spatial correlation of spherical harmonics coefficients.
We propose an efficient method to estimate source power spectral densities (PSDs) in a multi-source reverberant environment using a spherical microphone array. The proposed method utilizes the spatial correlation between the spherical harmonics (SH) coefficients of a sound field to estimate source PSDs. The use of the spatial cross-correlation of the SH coefficients allows us to employ the method in an environment with a higher number of sources compared to conventional methods. Furthermore, the orthogonality property of the SH basis functions saves the effort of designing specific beampatterns of a conventional beamformer-based method. We evaluate the performance of the algorithm with different number of sources in practical reverberant and non-reverberant rooms. We also demonstrate an application of the method by separating source signals using a conventional beamformer and a Wiener post-filter designed from the estimated PSDs.