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The degenerate unmixing estimation technique (DUET), enables facile sound source separation through two signal mixtures. However, in numerous practical situations, identifying peaks in DUET histograms is difficult, which in turn prevents effective source separation. Specifically, sound sources with short time percentages in mixtures are more unlikely to form peaks in a histogram. Besides, when the noise floor of mixtures is high, the height of the histogram peak may be reduced, which causes peak position bias and prevents effective source separation. In this study, unique methods are proposed to solve the aforementioned problems. A subhistogram is established for each time frame; thus, the original histogram is divided into a series of subhistograms. Two measurement indices are then proposed to identify the accurate attenuation and delay parameters for sound sources: maximum distribution, which is based on the infinity norm, and variance distribution, which is based on variances. The results verify that maximum distribution effectively highlights the peaks of instantaneous sound sources when the time percentage difference between sound sources is excessively high. In this scenario, the conventional histogram is unable to find the peaks. When a strong noise disturbance is present in mixtures, variance distribution can be employed to estimate peak positions with lower biases than those in the conventional histogram. In addition to more well-defined and intense peaks, the proposed method can also reduce the bias error by 71&#x0025; when the SNR is 0 dB. Variance distribution is more robust against noise disturbance compared to conventional histograms and can be adopted in a wide range of applications.

Unique Methods for Determining the Attenuation and Delay in Blind Source Separation Based on the Degenerate Unmixing Estimation Technique