8 ms·

I thought from the title that it goes into the mathematics. Unfortunately all the article says w.r.t math is a hand-wavy explanation of autocorrelation. But it

by bllguo 9y ago

I thought from the title that it goes into the mathematics. Unfortunately all the article says w.r.t math is a hand-wavy explanation of autocorrelation. But it was an interesting story about the life of Auto-Tune's creator.

biggieshellz 9y ago
See https://www.google.com/patents/US5973252 https://www.google.com/patents/US5973252 -- it looks like the trick is somehow simplifying the autocorrelation operation by fitting a quadratic curve.
jsjohnst 9y ago
Yeah, the “mathematical genius” is describing the author of Auto-Tune, not Auto-Tune itself. Through me off a bit too.
- pizza 9y ago
  I've worked with Hildebrand myself - he's one smart cookie, for sure. edit/tidbit: he told me that the interview process for hiring new developers goes like this: all the questions are straight out of K&R's C Programming Language, you have to get all of them correct, and so far only one programmer has :P
  - jsjohnst 9y ago
    I have an eidetic memory and have read that book multiple times, so there’s a fair chance I’d pass. That said, if I was given that interview as you described, I’d get up and walk out. Interviews like that prove absolutely nothing useful to evaluating a candidate and thus are a waste of time.
    - the_d00d 9y ago
      Why read it multiple times? Just close your eyes
      - mikestew 9y ago
        Because the eidetic memory only lasts for a few minutes. The commentor might have meant to use the phrase “photographic memory”, but that has thus far been shown to be myth. But, really, the post was about “I’m smart, and I’d just march right out of that interview”, ignoring that it was just a cute anecdote, so I guess it’s irrelevant. Nice catch, though. :-)
        jsjohnst 9y ago
        Mostly just a cute anecdote is fair, but wasn’t what I was replying to one too? ;) Seriously though, I’m tired of folks doing stupid counterproductive interviews and then parading them as a good thing.
      - jsjohnst 9y ago
        The other reply was right, because it’s not permanent. I remember a lot just reading, but for full eidetic it lasts a very short time.
  - hyperbovine 9y ago
    So he's hired one programmer.
    - narvind 9y ago
      0 He's obviously referring to himself.
      - pizza 9y ago
        no, he's hired one (other than himself), and she had been working there for ten years by the time we talked
        PhasmaFelis 9y ago
        So how long has been trying to hire another one? After 10 years I'd be getting desperate.
DonHopkins 9y ago
>"Seismic data processing involves the manipulation of acoustic data in relation to a linear time varying, unknown system (the Earth model) for the purpose of determining and clarifying the influences involved to enhance geologic interpretation. Coincident (similar) technologies include correlation (statics determination), linear predictive coding (deconvolution), synthesis (forward modeling), formant analysis (spectral enhancement), and processing integrity to minimize artifacts. All of these technologies are shared amongst music and geophysical applications." That is dramatic hand-waving, but it does help convey to non-programmers how dramatic an improvement the right algorithm can implement. It's true what the article says that pitch tracking was considered a difficult "holy grail" in 1995. I attended a talk about pitch tracking at Interval in 1996 by somebody whose name I don't remember any more. The speaker made the point that pitch is a perceptual -- not a mathematical -- concept, and it was hard but possible to do it in real time on a typical PC at the time (i.e. 90 MHZ IBM ThinkPad 760C). But he had done it, and everyone seemed impressed by his demo! ;) The article mentioned formant analysis. Maybe that's related to cepstral analysis, which is another way of tracking the pitch and formants of voice, and has its own cool nomenclature of secret code words. "Cepstral liftering" is basically two FFT's followed by an inverse FFT. If you take the complex FFT of a voice signal, the formants show up as two or three large "hills" in the spectrum, but the pitch manifests as higher frequency repeating furrows in the hills. (Which you want to filter out so you can analyze just the formants, or synthesize a different pitch into them (i.e. auto-tune), so you need to know the frequency of the change in the spectrum magnitude over time: another FFT!) http://www.phon.ucl.ac.uk/courses/spsci/matlab/lect10_files/image001.jpg http://www.phon.ucl.ac.uk/courses/spsci/matlab/lect10_files/... So you take a second FFT of the log of the first FFT, to get a "reverse spectrum" or "cepstrum" in the "quefrency" domain. The fundamental pitch shows up as one big spike in the cepstrum (with smaller spikes for its harmonics). Just "lifter" out the pitch spikes, then perform an inverse FFT to get back to the smooth low frequency formant hills with the high frequency pitch furrows removed. I'm sure there's a lot of "special sauce" in getting the math tweaked and tuned right so it actually sounds good and runs fast. https://stackoverflow.com/questions/4583950/cepstral-analysis-for-pitch-detection https://stackoverflow.com/questions/4583950/cepstral-analysi... The patent seems to be about autocorrelation, which is something different than cepstral analysis, but maybe they could be used together to get even better results. I don't know but would love to learn what the trade-offs and limitations the two techniques have. https://en.wikipedia.org/wiki/Cepstrum https://en.wikipedia.org/wiki/Cepstrum >The name "cepstrum" was derived by reversing the first four letters of "spectrum". Operations on cepstra are labelled quefrency analysis (aka quefrency alanysis), liftering, or cepstral analysis. https://surveillance7.sciencesconf.org/conference/surveillance7/01_a_history_of_cepstrum_analysis_and_its_application_to_mechanical_problems.pdf https://surveillance7.sciencesconf.org/conference/surveillan... "The original application was to the detection of echoes in seismic signals, where it was shown to be greatly superior to the autocorrelation function, because it was insensitive to the colour of the signal."

by bllguo 9y ago

biggieshellz 9y ago

See https://www.google.com/patents/US5973252 https://www.google.com/patents/US5973252 -- it looks like the trick is somehow simplifying the autocorrelation operation by fitting a quadratic curve.

jsjohnst 9y ago

Yeah, the “mathematical genius” is describing the author of Auto-Tune, not Auto-Tune itself. Through me off a bit too.

pizza 9y ago
I've worked with Hildebrand myself - he's one smart cookie, for sure. edit/tidbit: he told me that the interview process for hiring new developers goes like this: all the questions are straight out of K&R's C Programming Language, you have to get all of them correct, and so far only one programmer has :P
- jsjohnst 9y ago
  I have an eidetic memory and have read that book multiple times, so there’s a fair chance I’d pass. That said, if I was given that interview as you described, I’d get up and walk out. Interviews like that prove absolutely nothing useful to evaluating a candidate and thus are a waste of time.
  - the_d00d 9y ago
    Why read it multiple times? Just close your eyes
    - mikestew 9y ago
      Because the eidetic memory only lasts for a few minutes. The commentor might have meant to use the phrase “photographic memory”, but that has thus far been shown to be myth. But, really, the post was about “I’m smart, and I’d just march right out of that interview”, ignoring that it was just a cute anecdote, so I guess it’s irrelevant. Nice catch, though. :-)
      - jsjohnst 9y ago
        Mostly just a cute anecdote is fair, but wasn’t what I was replying to one too? ;) Seriously though, I’m tired of folks doing stupid counterproductive interviews and then parading them as a good thing.
    - jsjohnst 9y ago
      The other reply was right, because it’s not permanent. I remember a lot just reading, but for full eidetic it lasts a very short time.
- hyperbovine 9y ago
  So he's hired one programmer.
  - narvind 9y ago
    0 He's obviously referring to himself.
    - pizza 9y ago
      no, he's hired one (other than himself), and she had been working there for ten years by the time we talked
      - PhasmaFelis 9y ago
        So how long has been trying to hire another one? After 10 years I'd be getting desperate.

DonHopkins 9y ago

>"Seismic data processing involves the manipulation of acoustic data in relation to a linear time varying, unknown system (the Earth model) for the purpose of determining and clarifying the influences involved to enhance geologic interpretation. Coincident (similar) technologies include correlation (statics determination), linear predictive coding (deconvolution), synthesis (forward modeling), formant analysis (spectral enhancement), and processing integrity to minimize artifacts. All of these technologies are shared amongst music and geophysical applications." That is dramatic hand-waving, but it does help convey to non-programmers how dramatic an improvement the right algorithm can implement. It's true what the article says that pitch tracking was considered a difficult "holy grail" in 1995. I attended a talk about pitch tracking at Interval in 1996 by somebody whose name I don't remember any more. The speaker made the point that pitch is a perceptual -- not a mathematical -- concept, and it was hard but possible to do it in real time on a typical PC at the time (i.e. 90 MHZ IBM ThinkPad 760C). But he had done it, and everyone seemed impressed by his demo! ;) The article mentioned formant analysis. Maybe that's related to cepstral analysis, which is another way of tracking the pitch and formants of voice, and has its own cool nomenclature of secret code words. "Cepstral liftering" is basically two FFT's followed by an inverse FFT. If you take the complex FFT of a voice signal, the formants show up as two or three large "hills" in the spectrum, but the pitch manifests as higher frequency repeating furrows in the hills. (Which you want to filter out so you can analyze just the formants, or synthesize a different pitch into them (i.e. auto-tune), so you need to know the frequency of the change in the spectrum magnitude over time: another FFT!) http://www.phon.ucl.ac.uk/courses/spsci/matlab/lect10_files/image001.jpg http://www.phon.ucl.ac.uk/courses/spsci/matlab/lect10_files/... So you take a second FFT of the log of the first FFT, to get a "reverse spectrum" or "cepstrum" in the "quefrency" domain. The fundamental pitch shows up as one big spike in the cepstrum (with smaller spikes for its harmonics). Just "lifter" out the pitch spikes, then perform an inverse FFT to get back to the smooth low frequency formant hills with the high frequency pitch furrows removed. I'm sure there's a lot of "special sauce" in getting the math tweaked and tuned right so it actually sounds good and runs fast. https://stackoverflow.com/questions/4583950/cepstral-analysis-for-pitch-detection https://stackoverflow.com/questions/4583950/cepstral-analysi... The patent seems to be about autocorrelation, which is something different than cepstral analysis, but maybe they could be used together to get even better results. I don't know but would love to learn what the trade-offs and limitations the two techniques have. https://en.wikipedia.org/wiki/Cepstrum https://en.wikipedia.org/wiki/Cepstrum >The name "cepstrum" was derived by reversing the first four letters of "spectrum". Operations on cepstra are labelled quefrency analysis (aka quefrency alanysis), liftering, or cepstral analysis. https://surveillance7.sciencesconf.org/conference/surveillance7/01_a_history_of_cepstrum_analysis_and_its_application_to_mechanical_problems.pdf https://surveillance7.sciencesconf.org/conference/surveillan... "The original application was to the detection of echoes in seismic signals, where it was shown to be greatly superior to the autocorrelation function, because it was insensitive to the colour of the signal."