| Paper: | AE-P5.5 | ||
| Session: | Applications to Music II | ||
| Time: | Friday, May 21, 09:30 - 11:30 | ||
| Presentation: | Poster | ||
| Topic: | Audio and Electroacoustics: Applications to Music | ||
| Title: | BAYESIAN TWO SOURCE MODELING FOR SEPARATION OF N SOURCES FROM STEREO SIGNALS | ||
| Authors: | Aaron Master; Stanford University | ||
| Abstract: | We consider an enhancement to the DUET sound source separationsystem of Yilmaz and Rickard, which allowed for the separation ofN localized sparse sources given stereo mixture signals.Specifically, we expand the system and the related delay and scale subtraction scoring (DASSS) to consider cases whentwo sources, rather than one, are active at the same point in STFT time-frequency 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, and use this information in a Bayesian context to score the probability that two particular sources are active. We conclude with a musical example illustrating the benefit of our approach. | ||
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