Monaural speech separation using source-adapted models

Weiss, Ron J.; Ellis, Daniel P. W.

We propose a model-based source separation system for use on single channel speech mixtures where the precise source characteristics are not known a priori. We do this by representing the space of source variation with a parametric signal model based on the eigenvoice technique for rapid speaker adaptation. We present an algorithm to infer the characteristics of the sources present in a mixture, allowing for significantly improved separation performance over that obtained using unadapted source models. The algorithm is evaluated on the task defined in the 2006 Speech Separation Challenge [1] and compared with separation using source-dependent models.


Also Published In

2007 Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), October 21-24, 2007, New Paltz, NY

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Academic Units
Electrical Engineering
Published Here
June 27, 2012