A time-frequency blind signal separation method applicable to underdetermined mixtures of dependent sources

  • Authors:

  • Frédéric Abrard;Yannick Deville

  • Affiliations:

  • Laboratoire d'Astrophysique de Toulouse-Tarbes, Observatoire Midi-Pyrénées, Université Paul Sabatier, Edouard Belin, Toulouse, France;Laboratoire d'Astrophysique de Toulouse-Tarbes, Observatoire Midi-Pyrénées, Université Paul Sabatier, Edouard Belin, Toulouse, France

  • Venue:
  • Signal Processing
  • Year:
  • 2005

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Abstract

In this paper, we propose a new blind source separation (BSS) method called Time-Frequency Ratio Of Mixtures (TIFROM) which uses time-frequency (TF) information to cancel source signal contributions from a set of linear instantaneous mixtures of these sources. Unlike previously reported TF BSS methods, the proposed approach only requires slight differences in the TF distributions of the considered signals: it mainly requests the sources to be cancelled to be "visible", i.e. to occur alone in a tiny area of the TF plane, while they may overlap in all the remainder of this plane. By using TF ratios of mixed signals, it automatically determines these single-source TF areas and identifies the corresponding parts of the mixing matrix. This approach sets no conditions on the stationarity, independence or non-Gaussianity of the sources, unlike classical independent component analysis methods. It achieves complete or partial BSS, depending on the numbers N and P of sources and observations and on the number of visible sources. It is therefore of interest for underdetermined mixtures (i.e. N P), which cannot be processed with classical methods. Detailed results concerning mixtures of speech and music signals are presented and show that this approach yields very good performance.