Efficient model selection for speech enhancement using a deflation method for Nonnegative Matrix Factorization

Minje Kim, Paris Smaragdis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present a deflation method for Nonnegative Matrix Factorization (NMF) that aims to discover latent components one by one in order of importance. To do so we perform a series of individual decompositions, each of which stands for a deflation step. In each deflation we obtain a dominant component and a nonnegative residual, and then the residual is further used as an input to the next deflation in case we want to extract more components. With the help of the proposed additional inequality constraint on the residual during the optimization, the accumulated latent components at any given deflation step can approximate the input to some degree, whereas NMF with an inaccurate rank assumption often fail to do so. The proposed method is beneficial if we need efficiency in deciding the model complexity from unknown data. We derive multiplicative update rules similar to those of regular NMF to perform the optimization. Experiments on online speech enhancement show that the proposed deflation method has advantages over NMF: namely a scalable model structure, reusable parameters across decompositions, and resistance to permutation ambiguity.

Original languageEnglish (US)
Title of host publication2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages537-541
Number of pages5
ISBN (Electronic)9781479970889
DOIs
StatePublished - Feb 5 2014
Event2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014 - Atlanta, United States
Duration: Dec 3 2014Dec 5 2014

Publication series

Name2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014

Other

Other2014 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2014
CountryUnited States
CityAtlanta
Period12/3/1412/5/14

Keywords

  • Blind source separation
  • Speech enhancement

ASJC Scopus subject areas

  • Signal Processing
  • Information Systems

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