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How the cochlea computes (2024)

dissonances.blog

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Re: How the cochlea computes (2024)

#81

Post by fallingfrog »

jacquesm wrote: post #9
fallingfrog wrote: post #7

Earlier quoted context omitted.

I haven't noticed that effect, to be honest. Actually I think its the really low bass frequencies that are harder to tune- especially if you remove the harmonics and just leave the fundamental. Are you perhaps experiencing some high frequency hearing loss?

It's even more complex than that. The low notes are hard to tune because the fundamentals are very close to each other and you need to have super good hearing to match the beats, fortunately they sound for a long time so that helps. Missing fundamentals are a funny thing too, you might not be 'hearing' what you think you hear at all! The high notes are hard to tune because they sound very briefly (definitely on a pia…

Welll. On guitar you cant really use the "matching the beats" or the thing where you play the 4th on the string below and make them sound in unison, because if you do that all the way up the neck your guitar will be tuned to Just intonation instead of equal interval intonation and certain chords will sound very bad. A series of perfect 4ths and a perfect 3rd does not add up to an octave. Its better to reference everything to the low e string and just kind of know where the pitches are supposed to land.

That's a side note, the rest of what you wrote was very informative!

Re: How the cochlea computes (2024)

#82

Post by kiicia »

km3r wrote: post #79
edbaskerville wrote: post #21

To summarize: the ear does not do a Fourier transform, but it does do a time-localized frequency-domain transform akin to wavelets (specifically, intermediate between wavelet and Gabor transforms). It does this because the sounds processed by the ear are often localized in time. The article also describes a theory that human speech evolved to occupy an unoccupied space in frequency vs. envelope duration space. It mak…

> one would suspect that the specific characteristics of the human cochlea might be tuned to human speech while still being able to process environmental and animal sounds sufficiently well. I wonder if these could be used to better master movies and television audio such that the dialogue is easier to hear.

You are expecting too much, we still have no technology to do that, unless it’s about clarity of advertisement jingles /s

Re: How the cochlea computes (2024)

#83

Post by empiricus »

adornKey wrote: post #35

This subject has bothered me for a long time. My question to guys into acoustics was always: If the cochlea performs some kind of Fourier transform, what are the chances, that it uses sinus waves as a base for the vector-space? - if it did anything like that it could just as good use any slightly different wave-forms as a base for transformation. Stiffness and non-linearity will for sure take care that any ideal rubb…

well, cochlea is working withing the realm of biological and physical possibilities. basically it is a triangle through which waves are propagating, and sensors along the edge. smth smth this is similar to a filter bank of gabor filters that respond to rising freq along the triangle edge. ergo you can say fourier, but it only means sensors responding to different freq becasue of their location.

Re: How the cochlea computes (2024)

#84

Post by fennec-posix »

"It appears that human speech occupies a distinct time-frequency space. Some speculate that speech evolved to fill a time-frequency space that wasn’t yet occupied by other existing sounds."

I found this quite interesting, as I have noticed that I can detect voices in high-noise environments. E.g. HF Radio where noise is almost a constant if you don't use a digital mode.

Re: How the cochlea computes (2024)

#85

Post by kvakkefly »

xeonmc wrote: post #29
kazinator wrote: post #22

> A Fourier transform has no explicit temporal precision, and resembles something closer to the waveforms on the right; this is not what the filters in the cochlea look like. Perhaps the ear does someting more vaguely analogous to a discrete Fourier transforms on samples of data, which is what we do in a lot of signal processing. In signal processing, we take windowed samples, and do discrete transforms on these. The…

> analgous to the Pauli exclusion principle Did you mean the Heisenberg Uncertainty Principle instead? Or is there actually some connection of Pauli Exlusion Principle to conjugate transforms that I was’t aware of?

They are not connected afaik.

Re: How the cochlea computes (2024)

#86

Post by philip-b »

p0w3n3d wrote: post #2

Tbh I used to think that it does. For example, when playing higher notes, it's harder to hear the out-of-tune frequencies than on the lower notes.

No, it's vice versa. If two wind instruments play unison slightly out of tune from each other, it will be very noticeable. If the bass is slightly out of tune or mistakenly plays a different note a semitone up or down, it's easy to not notice it.

Re: How the cochlea computes (2024)

#88

Post by crazygringo »

edbaskerville wrote: post #21

To summarize: the ear does not do a Fourier transform, but it does do a time-localized frequency-domain transform akin to wavelets (specifically, intermediate between wavelet and Gabor transforms). It does this because the sounds processed by the ear are often localized in time. The article also describes a theory that human speech evolved to occupy an unoccupied space in frequency vs. envelope duration space. It mak…

Yeah, this article feels like it's very much setting up a ridiculous strawman.

Nobody who knows anything about signal processing has ever suggested that the ear performs a Fourier transform across infinite time.

But the ear does perform something very much akin to the FFT (fast Fourier transform), turning discrete samples into intensities at frequencies -- which is, of course, what any reasonable person means when they say the ear does a Fourier transform.

This article suggests it's accomplished by something between wavelet and Gabor. Which, yes, is not exactly a Fourier transform -- but it's producing something that is about 95-99% the same in the end.

And again, nobody would ever suggest the ear was performing the exact math that the FFT does, down to the last decimal point. But these filters still work essentially the same way as the FFT in terms of how they respond to a given frequency, it's really just how they're windowed.

So if anyone just wants a simple explanation, I would say yes the ear does a Fourier transform. A discrete one with windowing.

Re: How the cochlea computes (2024)

#89

Post by adornKey »

empiricus wrote: post #83
adornKey wrote: post #35

This subject has bothered me for a long time. My question to guys into acoustics was always: If the cochlea performs some kind of Fourier transform, what are the chances, that it uses sinus waves as a base for the vector-space? - if it did anything like that it could just as good use any slightly different wave-forms as a base for transformation. Stiffness and non-linearity will for sure take care that any ideal rubb…

well, cochlea is working withing the realm of biological and physical possibilities. basically it is a triangle through which waves are propagating, and sensors along the edge. smth smth this is similar to a filter bank of gabor filters that respond to rising freq along the triangle edge. ergo you can say fourier, but it only means sensors responding to different freq becasue of their location.

Yeah, but not only the frequency is important - the wave-form is very relevant. For example if your wave-form is a triangle, listerners will tell you that it is very noisy compared to a simple sinus. If you use sinus as a base of your vector space triangles really look like a noisy mix. My question is, if the basic elements are really sinus, or if the basic Eigen-Waves of the cochlea are other Wave-Forms (e.g. slightly wider or narrower than sinus, ...). If physics in the ear isn't linear, maybe sinus isn't the purest wave-form for a listener.

Most people in Physics only know sinus and maybe sometimes rectangles as a base for transformations, but mathematically you could use a lot of other things - maybe very similar to sinus, but different.

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