@INPROCEEDINGS{0731Burred2005,
	AUTHOR = {Juan José Burred and Thomas Sikora},
	TITLE = {On the Use of Auditory Representations for Sparsity-Based Sound Source Separation},
	BOOKTITLE = {IEEE Fifth Int. Conf. on Information, Communications and Signal Processing (ICICS '05)},
	YEAR = {2005},
	MONTH = dec,
	ADDRESS = {Bangkok, Thailand},
	PDF = {http://elvera.nue.tu-berlin.de/files/0731Burred2005.pdf},
	URL = {http://elvera.nue.tu-berlin.de/files/0731Burred2005.pdf},
	ABSTRACT = {Sparsity-based source separation algorithms often
rely on a transformation into a sparse domain to improve
mixture disjointness and therefore facilitate separation. To this
end, the most commonly used time-frequency representation has
been the Short Time Fourier Transform (STFT). The purpose of
this paper is to study the use of auditory-based representations
instead of the STFT. We first evaluate the STFT disjointness
properties for the case of speech and music signals, and show
that auditory representations based on the Equal Rectangular
Bandwidth (ERB) and Bark frequency scales can improve the
disjointness of the transformed mixtures.}
}