Source Separation with a Sensor Array Using Graphical Models and Subband Filtering

@inproceedings{Attias2002SourceSW,
  title={Source Separation with a Sensor Array Using Graphical Models and Subband Filtering},
  author={Hagai Attias},
  booktitle={NIPS},
  year={2002}
}
Source separation is an important problem at the intersection of several fields, including machine learning, signal processing, and speech technology. Here we describe new separation algorithms which are based on probabilistic graphical models with latent variables. In contrast with existing methods, these algorithms exploit detailed models to describe source properties. They also use subband filtering ideas to model the reverberant environment, and employ an explicit model for background and… CONTINUE READING
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References

Publications referenced by this paper.
Showing 1-10 of 11 references

A probabilistic approach to single channel blind signal separation

  • L. Deng Attias, A. Acero, J. C. Platt
  • 2003

A probabilistic approach to single channel blind signal separation.Proc

  • G.-J. Jang, T.-W. Lee, Y.-H
  • 2003

Audiovisual source separation via hidden Markov models

  • J. Hershey, M. Casey
  • Proc. NIPS
  • 2002

One Microphone Source Separation

  • Y.-H. Oh T.-W. Lee
  • 2001

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