Supervised source localization using diffusion kernels

Ronen Talmon, Israel Cohen, Sharon Gannot

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

46 Scopus citations

Abstract

Recently, we introduced a method to recover the controlling parameters of linear systems using diffusion kernels. In this paper, we apply our approach to the problem of source localization in a reverberant room using measurements from a single microphone. Prior recordings of signals from various known locations in the room are required for training and calibration. The proposed algorithm relies on a computation of a diffusion kernel with a specially-tailored distance measure. Experimental results in a real reverberant environment demonstrate accurate recovery of the source location.

Original languageEnglish
Title of host publication2011 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2011
Pages245-248
Number of pages4
DOIs
StatePublished - 2011
Event2011 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2011 - New Paltz, NY, United States
Duration: 16 Oct 201119 Oct 2011

Publication series

NameIEEE Workshop on Applications of Signal Processing to Audio and Acoustics

Conference

Conference2011 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics, WASPAA 2011
Country/TerritoryUnited States
CityNew Paltz, NY
Period16/10/1119/10/11

Keywords

  • Source localization
  • acoustic localization
  • diffusion geometry
  • diffusion kernel
  • manifold learning

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