I have an audio signal and I want to calculate the fundamental frequency contour for each syllable. In the related paper is said that only 9-time points are required. (9 values of frequency contour in each syllable).

As I saw in some papers, calculating fundamental frequency contour is equal to pitch contour.

Can someone please explain it to me what is it exactly?

Thanks in advance


closed as unclear what you're asking by Marcus Müller, lennon310, Matt L., jojek Apr 1 '17 at 16:22

Please clarify your specific problem or add additional details to highlight exactly what you need. As it's currently written, it’s hard to tell exactly what you're asking. See the How to Ask page for help clarifying this question. If this question can be reworded to fit the rules in the help center, please edit the question.

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    $\begingroup$ What paper you are referring to ? please share the link. question seems bit unclear. $\endgroup$ – arpit jain Mar 31 '17 at 9:42
  • $\begingroup$ What papers, to be exact. Not only the "related paper" would be important to know here, but also your "I saw in some papers" would probably best be backed by one or two references. We can't guess what you've read! Furthermore: define "equal to"; that's really important here. Usually, pitch and fundamental are related, but not necessarily the same (for every observer). So, your question isn't a "bit" unclear, it very much is unclear. $\endgroup$ – Marcus Müller Mar 31 '17 at 9:46
  • $\begingroup$ sorry for being unclear. the references are submitted. $\endgroup$ – reo1 Mar 31 '17 at 10:11
  • $\begingroup$ thanks! So, regarding your pitch-question: Really, voice pitch detection has been the topic of so many questions here, I think you should do a bit more research with the search function. Regarding the first question, these are mouse pups, that you're comparing to a paper about classifying speech of human Parkinson's patients – guess what, I don't know whether anything from the first paper applies to the second at all. You will have to make your point much, much clearer by explaining what exactly (mathematically, probably!) you're meaning with "9-time points". You still haven't … $\endgroup$ – Marcus Müller Mar 31 '17 at 11:06
  • $\begingroup$ defined "equal" and this is obviously a problem here, because you're already comparing papers on animal voices with human medicine signal processing, and the question really is whether you have any proof that things from the first source have much to do with things from the second. And you also haven't explained what you're looking for: description of baby mouse voices, or description of grown human voices, so this question really hasn't gotten much clearer. $\endgroup$ – Marcus Müller Mar 31 '17 at 11:07

Syllables might require a certain duration to be recognizable by humans. Over part of that time, voiced syllables might have a pitch, or a clear periodicity in waveform. Pitch can be described as having a fundamental frequency or F0 (the reciprocal of the perceived repetition period). Note that there a lots of other answers ont this Q&A site on various ways to measure pitch, and the potential problems related to such.

Pitch can change over time. If you measure pitch at several points in time (say 9 points for example) over the duration where a syllable is voiced, you might find that the measured pitch in fact has changed (or not). With those pitch measurements over time one could interpolate a curve (spline or polynomial regression, etc.) thru those measured points. You might end up making a bunch of different looking curves from different snippets of audio. One could also publish nice looking graphs of those interpolated curves and call the shapes of those curves contours.

Feed a lot of those nice looking pitch/F0 frequency contours (plus a large amount of other hopefully related data) to a machine learning algorithm, and it might be able to infer some possibly interesting correlations between things.

Or not.


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