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How the cochlea computes (2024)

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Re: How the cochlea computes (2024)

#41

Post by lukeinator42 »

rolph wrote: post #5
bloppe wrote: post #3

Man, I've been spreading disinformation for years.

the closest i have been, was acoustic phase discrimination by owls. there appears to be no software for this, its all hardware, the signal format flips as it travels through the anatomy.

also, the common ancestor of mammals and birds did not have a tympanic ear, so sound localization evolved differently in the avian vs. mammalian hearing systems. A good review is here: https://journals.physiology.org/doi/pdf/10.1152/physrev.0002.... How the brain calculates interaural time delays is actually an interesting problem as the time delays are so short, that it is less time than a neuron has to fire an action potential.

Re: How the cochlea computes (2024)

#42

Post by fwip »

AreYouElite wrote: post #23
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…

Do you believe it might be possible that the frequency band of human speech is not determined by such factors at all but more of a function of height? kids have higher voices adults have deeper voices. Similar to stringed instruments: viola high pitched and bass low pitched. I'm no expert in these matters just speculating...

It's not height, but vocal cord length and thickness. Longer vocal cords (induced by testosterone during puberty) vibrate more slowly, with a lower frequency/pitch.

Re: How the cochlea computes (2024)

#43

Post by JKCalhoun »

Chabsff wrote: post #16
adzm wrote: post #14

Earlier quoted context omitted.

the very simplest way to describe it: it is what turns a waveform (amplitude x time) to a spectrogram like on a stereo (amplitude x frequency)

And phase. People always forget about the phase as if it was purely imaginary.

Ha ha, as I understand it, phase is imaginary in a Fourier transform. Complex numbers are used and the imaginary portion does indeed represent phase.

I have been told that reversing the process — creating a time-based waveform — will not resemble (visually) the original due to this phase loss in the round-tripping. But then our brain never paid phase any mind so it will sound the same to our ears. (Yay, MP3!)

Re: How the cochlea computes (2024)

#44

Post by HarHarVeryFunny »

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…

> There is a trade off there between frequency and temporal precision

Sure, and the FFT isn't inherently biased towards one vs the other. If you take an FFT over a long time window (narrowband spectrogram) then you get good frequency resolution at the cost of time resolution, and vice versa for a short time window (wideband spectrogram).

For speech recognition ideally you'd want to use both since they are detecting different things. TFA is saying that this is in fact what our cochlea filter bank is doing, using different types of filter at different frequency ranges - better frequency resolution at lower frequencies where the formants are (carrying articulatory information), and better time resolution at the high frequencies generated by fricatives where frequency doesn't matter but accurate onset detection is useful for detecting plosives.

Re: How the cochlea computes (2024)

#46

Post by HarHarVeryFunny »

shermantanktop wrote: post #38

The thesis about human speech occupying less crowded spectrum is well aligned with a book called "The Great Animal Orchestra" ( https://www.amazon.com/Great-Animal-Orchestra-Finding-Origin... ). That author details how the "dawn chorus" is composed of a vast number of species making noise, but who are able to pick out mating calls and other signals due to evolving their vocalizations into unique sonic niches. It's qu…

Birds have also evolved to choose when to vocalize to best be heard - doing so earlier in urban areas where later there will be more traffic noise, and later in some forest environments to avoid being drowned out by the early rising noisy insects.

Re: How the cochlea computes (2024)

#47

Post by FarmerPotato »

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…

Is that an human understanding or is it just an AI that read the text and ignored the pictures?

Why do we need a summary in a post that adds nothing new to the conversation?

Re: How the cochlea computes (2024)

#48

Post by anigbrowl »

tryauuum wrote: post #8

man I need to finally learn what a Fourier transform is

Read this (which is free): The Scientist's and Engineer's Guide to Digital Signal Processing* https://www.dspguide.com

It's very comprehensive, but it's also very well written and walks you through the mechanics of Fourier transforms in a way that makes them intuitive.

Re: How the cochlea computes (2024)

#49

Post by pests »

FarmerPotato wrote: post #47
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…

Is that an human understanding or is it just an AI that read the text and ignored the pictures? Why do we need a summary in a post that adds nothing new to the conversation?

Are you saying your parent post was an AI summary? There is original speculation at the end and it didn’t come off that way to me.

Re: How the cochlea computes (2024)

#50

Post by dsp_person »

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…

Even if it is doing a wavelet transform, I still see that as made of Fourier transforms. Not sure if there's a good way to describe this.

We can make a short-time fourier transform or a wavelet transform in the same way either by:

- filterbank approach integrating signals in time

- take fourier transform of time slices, integrating in frequency

The same machinery just with different filters.

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