Blind source separation algorithms typically involve decorrelating time-aligned mixture signals. The usual assumption is that all sources are active at all times. However, if this is not the case, we show that the unique pattern of source activity/inactivity helps separation. Music is the most obvious example of sources exhibiting repetitive structure because it is carefully constructed. We present a novel source separation algorithm based on spatial time-time distributions that capture the repetitive structure in audio. Our method outperforms time-frequency source separation when source spectra are highly overlapping.

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