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Re: comodulation release of masking (CMR)
> >I think there is no consensus about the processing of CMR
> >stimuli although we recently argued that the envelope cross correlation
> >(not to mistake with the envelope cross covariance or correlation
> >coefficient) may be helpful in accounting for CMR data
> >(van de Par and Kohlrausch, 1998a/b: JASA 103 pp 3605-3620; 1573-1579).
> >In the paper on page 3605 we even describe a model that accounts
> >for CMR data.
> I think we are agreed that some form of cross-correlation mechanism is
> probably a good horse to bet on, I wonder though if you could clarify
> your distinction between different forms of cross-correlation.
The difference between both forms of correlation can
be seen looking at their definitions:
Cross correlation: rho = <xy> / sqrt(<x^2> <y^2>)
where x and y are the envelopes for which one wants to obtain
the envelope cross-correlation.
Cross covariance: r = <XY> / sqrt(<X^2> <Y^2>)
where X = x - <x> and Y = y - <y>
(Note that the cross covariance is also called the
In other words: for the cross covariance the mean (or DC)
component of the envelopes is first removed (the -<x> and
-<y> terms in the equation).
This removal of the DC component is what is problematic about
the cross covariance in my opinion. To see this, consider two tonal
carriers at different frequencies that are modulated
with the same sinusoidal modulator except that the
modulators differ in phase by either zero or pi radians.
Now subjects have to detect the change in modulator phase.
Independent of the modulation depth the envelope cross covariance
will either be +1 or -1, indicating
that detectability of modulator phase difference
is independent of modulation depth. This is a problem
because eventually, when the modulation depth is very small
subjects will have great difficulties detecting modulator
The envelope cross correlation doesn't suffer
from these problems because the envelope cross correlation
will depend on the modulation depth.
The difference between the two definitions of correlation
has also been studied in relation to binaural detection
at high frequencies where processing of envelopes is
also assumed to be important. A very interesting
study has been published by Bernstein and Trahiotis
on this topic (1996; JASA 100, 1754-1763) where
behavioural data show that the envelope
cross correlation gives a much better account of
high frequency binaural detection data then the covariance.
> cross-correlation mechanism I proposed in Todd (1996, Network: Computation
> in Neural Systems. 7, 349-356) was a product-moment on the cosine phase
> of the envelope modulation power spectrum.
If I read this correctly you calculate correlations between envelope spectra
instead of correlations between temporal envelopes.
In that case the DC component of the envelope will be preserved
within the spectrum. As far as I can see there will be no
problems with regard to the type of stimuli that I described
Steven van de Par
IPO-Center for research on user-system interaction
Den Dolech 2
5612 AZ Eindhoven
Phone: +31 40 2475215
Fax: +31 40 2431930
> This had the advantage that
> one didn't need to have delay lines or some other storage mechanism since
> if one uses acausal impulse response function (or non-linear phase response
> transfer function) for the modulation filter, this is effectively a kind of
> memory. Further, the cosine phase spectrum locks into that of the envelope
> thus preserving sensitivity to phase effects in streaming (e.g. in an
> alternating A B A B sequence). I did play around with some other metrics,
> e.g. Euclidean distance, but did not conclude that there was any advantage
> over the product-moment, although I did consider how such a cross-correlation
> mechanism might be instantiated neurally.
> Best wishes
> University of Manchester
> M13 9PL
> Tel. +44 (0)161 275 2557
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