Underdetermined Sound Source Separation Using Power Spectrum Density Estimated by Combination of Directivity Gain
Yusuke Hioka, Ken’ichi Furuya, Kayoko Kobayashi, Kenta Niwa, Yoichi Haneda · IEEE Transactions on Audio Speech and Language Processing · 2013
A method for separating underdetermined sound sources based on a novel power spectral density (PSD) estimation is proposed. The method enables up toM(M-1)+1 sources to be separated when we use a microphone array ofMsensors and a Wiener post-filter calculated by the estimated PSDs. The PSD of a beamformer's output is modelled by a mixture of source PSDs multiplied by the beamformer's directivity gain in the particular angle where each source is located. Based on this model, the PSD of each sound source is estimated from the PSD of multiple fixed beamformers' outputs using the difference in the combination of directivity gains. Simulation results proved that the proposed method effectively separated up toM(M-1)+1 sound sources if the fixed beamformers were appropriately selected. Experiments were also conducted in a reverberant chamber to ensure the proposed method was also effective in practical use.