Bayesian Two-Source Models for Stereo Sound Source Separation of N Sources

Aaron S. Master¹

EE 391 Report, Summer 2003

Abstract:

We presently consider an enhancement to the DUET sound source separation system [1]. Specifically, we expand the system and the related delay and scale subtraction scoring (DASSS) [2] to allow sounds from exactly two sources to be active at the same point in time-frequency (STFT) space. We begin with a review of the DUET system and its sparsity and independence assumptions. We then consider how the DUET system and DASSS respond when faced with two active sources at the same point in time-frequency space. For this case, we show the important result that the DUET and DASSS data may reveal which two sources are active. To exploit this result, we present a Bayesian framework for determining the most likely sources given DUET and DASS data. We then show how to use this framework on DASSS data. We conclude with an example showing the efficacy of using DASS data for determining and demixing two active sources.