Convolutive Audio Source Separation Using Robust ICA and Reduced Likelihood Ratio Jump

  • Dimitrios Mallis
  • Thomas Sgouros
  • Nikolaos Mitianoudis
Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 475)


Audio source separation is the task of isolating sound sources that are active simultaneously in a room captured by a set of microphones. Convolutive audio source separation of equal number of sources and microphones has a number of shortcomings including the complexity of frequency-domain ICA, the permutation ambiguity and the problem’s scalabity with increasing number of sensors. In this paper, the authors propose a multiple-microphone audio source separation algorithm based on a previous work of Mitianoudis and Davies [1]. Complex FastICA is substituted by Robust ICA increasing robustness and performance. Permutation ambiguity is solved using the Likelihood Ration Jump solution, which is now modified to decrease computational complexity in the case of multiple microphones.


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Copyright information

© IFIP International Federation for Information Processing 2016

Authors and Affiliations

  • Dimitrios Mallis
    • 1
  • Thomas Sgouros
    • 1
  • Nikolaos Mitianoudis
    • 1
  1. 1.Department of Electrical and Computer EngineeringDemocritus University of ThraceXanthiGreece

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