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@CONFERENCE{Krijnders2008a,
  author = {Krijnders, J.D. and Niessen, M.E. and Andringa, T.C.},
  title = {A grouping approach to harmonic complexes},
  booktitle = {Proc. of Acoustics '08},
  year = {2008},
  abstract = {Humans seem to perform sound-source separation for quasi-periodic
	sounds, such as speech, mostly on harmonicity cues. To model this
	function, most machine algorithms use a pitch-based approach to group
	the speech parts of the spectrum. In these methods the pitch is obtained
	either explicitly, in autocorrelation methods, or implicitly, as
	in harmonic sieves. If the estimation of pitch is wrong, the grouping
	will fail as well. In this paper we show a method that performs harmonic
	grouping without first calculating the pitch. Instead a pitch estimate
	is associated with each grouping hypothesis.
	
	Making the grouping independent of the pitch estimate makes it more
	robust in noisy settings.
	
	The algorithm obtains possible harmonics by tracking energy peaks
	in a cochleogram. Co-occuring harmonics are compared in terms of
	frequency difference. Grouping hypotheses are formed by combining
	harmonics with similar frequency differences. Consistency checks
	are performed on these hypotheses and hypotheses with compatible
	properties are combined into harmonic complexes. Every harmonic complex
	is evaluated on the number of the harmonics, the number of subsequent
	harmonics and the presence of a harmonic at the pitch position. By
	using the number of subsequent harmonics octave errors are prevented.
	
	Multiple concurrent harmonic complexes can be found as long as the
	spectral overlap is small.},
  owner = {dirkjan},
  timestamp = {2008.06.27}
}

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