
Fundamental frequency estimation and supervised learning - horigome
http://obogason.com/fundamental-frequency-estimation-and-machine-learning/
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kevin_thibedeau
There is a good way to make the harmonic product spectrum more robust to the
effects of noise. You generate a synthetic spectrum starting from a histogram
of zero crossing intervals that has been "smeared" back into a continuous
signal with Gaussian peaks by applying a kernel density estimate. The result
can then be passed through the HPS to find the fundamental. The decorrelated
zero crossings caused by noise are much less problematic than working with the
HPS of the original signal.

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horigome
Sounds interesting, do you an example of the performance you might expect from
such a system? I must say that out out of the estimators I tried, HPS is the
most difficult to deal with. You need information about how the harmonics are
related to the fundamental and how many harmonics you expect before applying
the algorithm. Maybe there are some adaptive methods that exists for this job
but HPS is intrinsically ad-hoc, which is not very nice.

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jeremysalwen
The MPM algorithm is an even better variation on autocorrelation than YIN.

It picks the first peak of the autocorrelation after zero-crossing that is
greater than k*(max peak). k~=0.9

[http://www.cs.otago.ac.nz/tartini/papers/A_Smarter_Way_to_Fi...](http://www.cs.otago.ac.nz/tartini/papers/A_Smarter_Way_to_Find_Pitch.pdf)

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robhack
Is there a way to download all the instrument samples from the University of
Iowa in a single archive file?

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horigome
Unfortunately they only provide .zips for each instrument in Post-2012
category. You can download them at the bottom of each page f.x.
[http://theremin.music.uiowa.edu/MIS-
Pitches-2012/MISEbClarin...](http://theremin.music.uiowa.edu/MIS-
Pitches-2012/MISEbClarinet2012.html) There's no compressed file option for the
Pre-2012.

It might be easier to make a scraper then downloading all of the files
individually.

