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Do you know of any algorithms for audio processing that make use of peaks in auto-correlation function? I am currently involved in research on mapping methodology for dynamic algorithms. I came recently over an algorithm for detection of fundamental frequency in audio signals, which has a dynamic structure I am looking for - the execution time of the algorithm varies with the number of peaks in the signal's auto-correlation:

while (i < hsize)

    // Search for peaks in auto-correlation:
    if((r[i] > 0) && (r[i]>r[i-1]) && (r[i]>=r[i+1])){

            temp = 0.25f*(r[i+1]-r[i-1]);
            temp = r[i] - temp*temp/(0.5f*(r[i+1]+r[i-1]) - r[i]);
            n = n1[i] + n2[i];
            if ((rmax*n) < (temp*nmax)) {imax=i; rmax=temp; nmax=n;}.

            i++;}
    else{i++;}

This would be perfect as a studying example for my methodology, but the problem is that there is only a couple of lines inside the loop, so the overhead of adding my techniques becomes too big for the problem of this size. Now I am wondering if there exist any similar algorithms in audio processing, i.e. also making use of peaks in auto-correlation function but perform more extensive calculations for each peak?

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    $\begingroup$ Dear colleagues, I am sorry that my post do not have any greeting. I could actually not add any - it disappears from the posted text! $\endgroup$ Commented Nov 25, 2014 at 9:46
  • $\begingroup$ Elena, i would suggest that many pitch-detection algorithms use some form of auto-correlation and must look at every peak of any significance and make decisions regarding those peaks (like picking just one of the peaks and then interpolating the precise location). $\endgroup$ Commented Nov 25, 2014 at 17:55
  • $\begingroup$ Thank you Robert! This is a good hint, I will look closer at pitch-detection algorithms! $\endgroup$ Commented Nov 26, 2014 at 9:04
  • $\begingroup$ @ElenaHammari Greetings and thanks are automatically removed because they are considered a distraction from the question. Just ask the question and thank people by clicking the upvote arrows. $\endgroup$
    – endolith
    Commented Dec 26, 2014 at 15:36

1 Answer 1

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The YIN Algorithm could be of interest to you. It's based on autocorrelation and is used for estimating the fundamental frequency.

A. de Cheveigné, H. Kawahara: YIN, a fundamental frequency estimator for speech and music, Proceedings of ICMC 2005. Download PDF.

A C++ implementation is also available.

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  • $\begingroup$ Thank you, Frank! Actually I already have YIN algorithm included in the same library as the algorithm above (which is documented as McLeod/Wyvill normalization scheme). I have profiled the YIN algorithm too, but did not test my methodology on it yet. And it seems that the version of YIN that I have is not the full one (step 6 of the algorithm is excluded), so it is indeed possible to extend further. Thank you for the link to the code! $\endgroup$ Commented Nov 26, 2014 at 13:26
  • $\begingroup$ I have now checked the YIN algorithm in my library and it still gives the same problem, although the results are better. Hope the full version of the algorithm will help :). $\endgroup$ Commented Nov 27, 2014 at 11:05
  • $\begingroup$ @ElenaHammari: If this answer helped, please consider accepting it. $\endgroup$
    – Peter K.
    Commented Mar 26, 2015 at 12:25

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