Sound Source Separation by Using Matched Beamforming and Time-Frequency Masking

This paper proposes a two-stage algorithm to separate two sound sources by using matched beamforming and time-frequency masking techniques. At first, beamforming was used to separate the sound mixtures back to the original sources while preserving the original contents to the maximum extent. The residual interference was then suppressed by the time-frequency masking technique. A sequential least squares method was used in developing a matched beamformer to estimate the relative transfer function (RTF). From experimental results, it has been shown that the proposed method exhibits improved performance in sound source separation compared to conventional methods. Signal enhanced factor (SEF) was improved by an average of 8.39 dB over the baseline.