Academic Commons

Articles

Source Separation Based on Binaural Cues and Source Model Constraints

Weiss, Ron J.; Mandel, Michael I.; Ellis, Daniel P. W.

We describe a system for separating multiple sources from a two-channel recording based on interaural cues and known characteristics of the source signals. We combine a probabilistic model of the observed interaural level and phase differences with a prior model of the source statistics and derive an EM algorithm for finding the maximum likelihood parameters of the joint model. The system is able to separate more sound sources than there are observed channels. In simulated reverberant mixtures of three speakers the proposed algorithm gives a signal-to-noise ratio improvement of 2.1 dB over a baseline algorithm using only interaural cues.

Files

Also Published In

Title
9th annual conference of the International Speech Communication Association 2008: (INTERSPEECH 2008) Brisbane, Australia, 22-26 September 2008

More About This Work

Academic Units
Electrical Engineering
Publisher
International Speech Communication Association
Published Here
June 27, 2012
Academic Commons provides global access to research and scholarship produced at Columbia University, Barnard College, Teachers College, Union Theological Seminary and Jewish Theological Seminary. Academic Commons is managed by the Columbia University Libraries.