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Re: About importance of "phase" in sound recognition

Re: Below, while I think a frequency tiling that is somewhat like a wavelet is quite appropriate, in fact something more like a tiling of .7 Bark at low frequencies and 1 ERB at higher frequencies, with attention paid to the slope of the filter skirts, would be ideal, I don’t think a wavelet is idea for auditory analysis, since the ear consists of a set of heavily overlapped, far from 1:1 and onto “bands”.  I know from working on loudness models that you must have a filter at each 1/3 ERB (at higher frequencies, let’s stick to something like .7 bark at low, please) with the appropriate response CENTERED on that frequency. Using minimum-phase seems ok for this.


But, with wavelet transforms, you’re going to have 1:1 performance, and spacing accordingly, with critical sampling properties. This is not going to handle edges of bands very well in my experience.


In particular, I’m objecting to the 1:1 and onto properties of the wavelet, they do not match how the ear works.   Of course, if you must do exact reconstruction, that’s a different issue.



James D. Johnston  (jj@xxxxxxx)


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Those interested in the mathematical basis of phase perception might like to look at a paper by Martin Reimann that appeared in JASA a few years ago. After demonstrating that the cochlea preforms a wavelet transform rather than a windowed Fourier transform, he goes on to describe how phase operates in the wavelet representation of auditory processing.



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