Hi there, this is a technique for calculating the noise floor of a spectrum, and extracting the peaks.
It'd be used pretty much like I04.Noie Gate Miller's example, that has the "mask" table with a constant multiplier. We'd have instead this "noise-floor" block of audio, also multiplied by a constant.
To get the noise floor, we take the magnitude (or power) spectrum and get the median of small bits of it, like every 32 samples. So the values of every 32 samples would be the median of that section...
this is where I got this from, check page 4 and 5 http://homepages.cae.wisc.edu/~sethares/software/SpectralTools.pdf
this would be kinda like using the [median] or [median_n] objects, but over audio blocks and not number lists.
Since there's the need of calculating this in and using the result back in the same block round into the audio chain, I can't put the spectrum into a table, and then calculate the median over bits of it.
But then, how to do it? Should I be able to pull this out only if I write a "median~" or [noise_floor~] external?
Or somehow there's another way to do this with some existing external, or a similar technique, or even some audio math trick using [fexpr~] or something?
This has to do with the other post I did about a project that attempts to isolate notes into a chord in a spectrum, something like melodyne is does.
thanks Alex
here's my patch by the way.
I can't attach files to the list, right? I'm sending the code in the body of the message.
I guess one way would be to write an external that would give me back this block of audio with the median of each section. I'd replace it in the [avg~] object in the patch bellow. Cheers.
noise-floor_filter.pd
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2011/12/20 Alexandre Torres Porres porres@gmail.com
Hi there, this is a technique for calculating the noise floor of a spectrum, and extracting the peaks.
It'd be used pretty much like I04.Noie Gate Miller's example, that has the "mask" table with a constant multiplier. We'd have instead this "noise-floor" block of audio, also multiplied by a constant.
To get the noise floor, we take the magnitude (or power) spectrum and get the median of small bits of it, like every 32 samples. So the values of every 32 samples would be the median of that section...
this is where I got this from, check page 4 and 5 http://homepages.cae.wisc.edu/~sethares/software/SpectralTools.pdf
this would be kinda like using the [median] or [median_n] objects, but over audio blocks and not number lists.
Since there's the need of calculating this in and using the result back in the same block round into the audio chain, I can't put the spectrum into a table, and then calculate the median over bits of it.
But then, how to do it? Should I be able to pull this out only if I write a "median~" or [noise_floor~] external?
Or somehow there's another way to do this with some existing external, or a similar technique, or even some audio math trick using [fexpr~] or something?
This has to do with the other post I did about a project that attempts to isolate notes into a chord in a spectrum, something like melodyne is does.
thanks Alex
stupid bug; dsp $1 instead of dsp 1 on loadbang
now corrected:
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2011/12/20 Alexandre Torres Porres porres@gmail.com
Hi there, this is a technique for calculating the noise floor of a spectrum, and extracting the peaks.
It'd be used pretty much like I04.Noie Gate Miller's example, that has the "mask" table with a constant multiplier. We'd have instead this "noise-floor" block of audio, also multiplied by a constant.
To get the noise floor, we take the magnitude (or power) spectrum and get the median of small bits of it, like every 32 samples. So the values of every 32 samples would be the median of that section...
this is where I got this from, check page 4 and 5 http://homepages.cae.wisc.edu/~sethares/software/SpectralTools.pdf
this would be kinda like using the [median] or [median_n] objects, but over audio blocks and not number lists.
Since there's the need of calculating this in and using the result back in the same block round into the audio chain, I can't put the spectrum into a table, and then calculate the median over bits of it.
But then, how to do it? Should I be able to pull this out only if I write a "median~" or [noise_floor~] external?
Or somehow there's another way to do this with some existing external, or a similar technique, or even some audio math trick using [fexpr~] or something?
This has to do with the other post I did about a project that attempts to isolate notes into a chord in a spectrum, something like melodyne is does.
thanks Alex
Hi Alex
I've been reading all your posts lately. Very interesting--I will look forward to your new phase vocorder stuff, when I get free time and enough rest.
Have you considered weighted median filtering? It's a non-linear filter structure that takes non-negative integers as arguments. At each sample, you create a list of samples, the adjacent values taken according to the filter arguments. Then, count through the list finding the lowest value each time, and add up the filter weights until you cross the median.
The purpose of weighting is to allow some more flexibility to shape the spectrum and prefer values that are closer to the original signal. It still has the same ability to reject outliers if you select good weights.
I had made a badly written external, and a cpu-hungry abstraction (with fexpr~ and a fixed number of weights) a while back. I'd be happy to dig up the code and algorithm after work today.
There's just two things that sound difficult in this application:
How to handle the endpoints of the signal blocks?
The statistical properties of median and weighted median filters
are tough to describe analytically. If you've got to justify your choice of this one component... it may take some research. Estimating threshold values with mean/variance calculations are much easier analytically.
Chuck
On Tue, Dec 20, 2011 at 5:29 PM, Alexandre Torres Porres porres@gmail.com wrote:
Hi there, this is a technique for calculating the noise floor of a spectrum, and extracting the peaks.
It'd be used pretty much like I04.Noie Gate Miller's example, that has the "mask" table with a constant multiplier. We'd have instead this "noise-floor" block of audio, also multiplied by a constant.
To get the noise floor, we take the magnitude (or power) spectrum and get the median of small bits of it, like every 32 samples. So the values of every 32 samples would be the median of that section...
this is where I got this from, check page 4 and 5 http://homepages.cae.wisc.edu/~sethares/software/SpectralTools.pdf
this would be kinda like using the [median] or [median_n] objects, but over audio blocks and not number lists.
Since there's the need of calculating this in and using the result back in the same block round into the audio chain, I can't put the spectrum into a table, and then calculate the median over bits of it.
But then, how to do it? Should I be able to pull this out only if I write a "median~" or [noise_floor~] external?
Or somehow there's another way to do this with some existing external, or a similar technique, or even some audio math trick using [fexpr~] or something?
This has to do with the other post I did about a project that attempts to isolate notes into a chord in a spectrum, something like melodyne is does.
thanks Alex
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On Wed, Dec 21, 2011 at 11:15 AM, Charles Henry czhenry@gmail.com wrote:
I had made a badly written external, and a cpu-hungry abstraction (with fexpr~ and a fixed number of weights) a while back. I'd be happy to dig up the code and algorithm after work today.
Here's the abstraction: wmed5~.pd Below is also a pasted test patch. How it works: it computes all branches! Just for fun, because it's not something that scales well with more taps, but works.
wmed5~.pd
#N canvas 0 0 765 642 10; #X obj 150 132 t b b; #X obj 189 132 loadbang; #X obj 452 188 expr $f1+$f2+$f3+$f4+$f5; #X obj 455 225 expr int(($f1+1)/2); #X text 591 227 median index; #X obj 11 33 inlet~; #X obj 62 230 fexpr~ $f3*($x1>$x1[-1]) + $f4*($x1>$x1[-2]) + $f5*($x1>$x1[-3])
- $f6*($x1>$x1[-4]) ; $f2*($x1<=$x1[-1]) + $f4*($x1[-1]>$x1[-2]) +
$f5*($x1[-1]>$x1[-3]) + $f6*($x1[-1]>$x1[-4]) ; $f2*($x1<=$x1[-2])
- $f3*($x1[-1]<=$x1[-2]) + $f5*($x1[-2]>$x1[-3]) + $f6*($x1[-2]>$x1[-4])
; $f2*($x1<=$x1[-3]) + $f3*($x1[-1]<=$x1[-3]) + $f4*($x1[-2]<=$x1[-3])
- $f6*($x1[-3]>$x1[-4]) ; $f2*($x1<=$x1[-4]) + $f3*($x1[-1]<=$x1[-4])
- $f4*($x1[-2]<=$x1[-4]) + $f5*($x1[-3]<=$x1[-4]);
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wmed5-test.pd
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On Wed, Dec 21, 2011 at 11:15 AM, Charles Henry czhenry@gmail.com wrote:
- How to handle the endpoints of the signal blocks?
I've thought this over, and concluded that it really doesn't matter, for the case of the magnitude of power spectral density.
Any high or low values of the spectrum at DC and at the Nyquist frequency will be rejected, because of the symmetry of the Fourier transform about these points.
You'd probably treat the blocks as circular buffers for the purpose of median filtering your spectrum. It stays a little neater that way anyhow, with no samples held over from the previous block.
- The statistical properties of median and weighted median filters
are tough to describe analytically. If you've got to justify your choice of this one component... it may take some research. Estimating threshold values with mean/variance calculations are much easier analytically.
I've also thought this over, and the median filter is the black magic of non-linear filtering. It rejects some bad points in the data no matter how bad they are which makes it robust and really practical, but quantifying the effects is some kind of arcane secret.
Another way to look at it is what it does for your spectrum's continuity--it might be good to rid of some of the variability in the noise floor estimation, just making the spectrum smoother, which the median filter certainly does. I wonder if there could be something analogous for smoothing out phase in a spectrum?
On Tue, Dec 20, 2011 at 5:29 PM, Alexandre Torres Porres porres@gmail.com wrote:
Hi there, this is a technique for calculating the noise floor of a spectrum, and extracting the peaks.
It'd be used pretty much like I04.Noie Gate Miller's example, that has the "mask" table with a constant multiplier. We'd have instead this "noise-floor" block of audio, also multiplied by a constant.
To get the noise floor, we take the magnitude (or power) spectrum and get the median of small bits of it, like every 32 samples. So the values of every 32 samples would be the median of that section...
this is where I got this from, check page 4 and 5 http://homepages.cae.wisc.edu/~sethares/software/SpectralTools.pdf
this would be kinda like using the [median] or [median_n] objects, but over audio blocks and not number lists.
Since there's the need of calculating this in and using the result back in the same block round into the audio chain, I can't put the spectrum into a table, and then calculate the median over bits of it.
But then, how to do it? Should I be able to pull this out only if I write a "median~" or [noise_floor~] external?
Or somehow there's another way to do this with some existing external, or a similar technique, or even some audio math trick using [fexpr~] or something?
This has to do with the other post I did about a project that attempts to isolate notes into a chord in a spectrum, something like melodyne is does.
thanks Alex
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Hi there, I had no idea there was such a thing as the [pack~] & [unpack~] objects. I was about to ask about something like this, or propose it, because it is very cool the idea of acting on audio blocks as if they were lists, and do all sorts of operations we cant with audio objects.
Anyway, now that I there is such a thing, and since I already had programmed the median filter I needed with control objetcs... voilá! I have the thing working well.
But then, I need to delay the signal, since [pack~]/[unpack~] delays a block of audio.
My question is, is it possible to have it done without the delays?
thanks a lot, here's my code for you people to check this out.
==============================================
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Le 2011-12-23 à 18:53:00, Alexandre Torres Porres a écrit :
Hi there, I had no idea there was such a thing as the [pack~] & [unpack~] objects. I was about to ask about something like this, or propose it, because it is very cool the idea of acting on audio blocks as if they were lists,
Also, [#from~] and [#to~] can take multiple signals and turn them into columns inside matrices, and back into multiple signals.
http://gridflow.ca/help/%23from~-help.html http://gridflow.ca/help/%23to~-help.html
| Mathieu BOUCHARD ----- téléphone : +1.514.383.3801 ----- Montréal, QC
Le 2011-12-20 à 21:29:00, Alexandre Torres Porres a écrit :
this would be kinda like using the [median] or [median_n] objects, but over audio blocks and not number lists.
Ok, lots of heavy details below...
The way [median] and [median_n] are built, they take a lot of time. Sorting each window of 32 elements is slow with any full sort. Even the usually slow process of putting elements one by one in a sorted array is faster than any full sort like qsort() or [sort], in this kind of situation, because you need to look at the result of the sort after each insertion/removal.
But a sort based on binary-trees will make your median filter able to compete with the speed of FFT, for example. You keep your sorted «array» as a sorted binary tree and this makes it fast to insert, delete, and find the middle. But you can't do that with C++'s std::map because it offers no way to find the middle quickly... you'd need something special.
There may be ways to bend quicksort so that it can do many similar sorts quickly, but you can't do that with qsort() nor anything based on it.
I don't know how zexy's [sort]. Apparently it doesn't use the quicksort method that I assumed it did, it uses the shellsort method instead, which is sometimes slower, sometimes faster. I wonder whether it could speed up your task if you made a kind of [median_n] that would reuse the already-sorted list to speed up the next sort. (This would not improve a quicksort, but I wonder whether it'd improve [sort]).
Generally, median-based methods are harder to work with, as they involve lots of comparisons and swaps and such, by sorting or by doing things that are like sorting ; whereas mean-based methods involve simple fast passes of addition and multiplication. But both give quite different results, in many situations.
Since there's the need of calculating this in and using the result back in the same block round into the audio chain, I can't put the spectrum into a table, and then calculate the median over bits of it.
with [tabsend~] and a [bang~], then you can send a whole block into the message domain, compute it, and get it back as a signal, one block later.
But then, how to do it? Should I be able to pull this out only if I write a "median~" or [noise_floor~] external?
Or somehow there's another way to do this with some existing external, or a similar technique, or even some audio math trick using [fexpr~] or something?
I don't think you can do any reasonable sort using [fexpr~]... except perhaps a strange undecipherable network of a hundred [fexpr~] or so. I think it's easier to write an external.
This has to do with the other post I did about a project that attempts to isolate notes into a chord in a spectrum, something like melodyne is does.
So, why is a mean (average) not good enough, while a median would be good enough ? It's possible, but I'd like to hear an explanation.
| Mathieu BOUCHARD ----- téléphone : +1.514.383.3801 ----- Montréal, QC
So, why is a mean (average) not good enough, while a median would be good
enough ?
It's possible, but I'd like to hear an explanation.
I'd need to test and compare, all I know is that I tested [avg~] and compared it to sethares' objects in MAX, that do this median filter, and they seem to sound better over there.
But these objects (GNU General Public License v2.0) are actually codes in java,
for(int i=0; i<framesize; i++) { // set the output magnitude by if(i % medlen == 0){ // taking moving median of input for(int ij=0; ij<medlen; ij++) { // this takes median thesevals[ij] = magformed[i+ij]; // of medlen elements } noisefloor[i] = (float)(Statistics.median(thesevals)); } else { // advance median by medlen steps noisefloor[i] = noisefloor[i-1]; // keeping same value
2011/12/22 Mathieu Bouchard matju@artengine.ca
Le 2011-12-20 à 21:29:00, Alexandre Torres Porres a écrit :
this would be kinda like using the [median] or [median_n] objects, but
over audio blocks and not number lists.
Ok, lots of heavy details below...
The way [median] and [median_n] are built, they take a lot of time. Sorting each window of 32 elements is slow with any full sort. Even the usually slow process of putting elements one by one in a sorted array is faster than any full sort like qsort() or [sort], in this kind of situation, because you need to look at the result of the sort after each insertion/removal.
But a sort based on binary-trees will make your median filter able to compete with the speed of FFT, for example. You keep your sorted «array» as a sorted binary tree and this makes it fast to insert, delete, and find the middle. But you can't do that with C++'s std::map because it offers no way to find the middle quickly... you'd need something special.
There may be ways to bend quicksort so that it can do many similar sorts quickly, but you can't do that with qsort() nor anything based on it.
I don't know how zexy's [sort]. Apparently it doesn't use the quicksort method that I assumed it did, it uses the shellsort method instead, which is sometimes slower, sometimes faster. I wonder whether it could speed up your task if you made a kind of [median_n] that would reuse the already-sorted list to speed up the next sort. (This would not improve a quicksort, but I wonder whether it'd improve [sort]).
Generally, median-based methods are harder to work with, as they involve lots of comparisons and swaps and such, by sorting or by doing things that are like sorting ; whereas mean-based methods involve simple fast passes of addition and multiplication. But both give quite different results, in many situations.
Since there's the need of calculating this in and using the result back
in the same block round into the audio chain, I can't put the spectrum into a table, and then calculate the median over bits of it.
with [tabsend~] and a [bang~], then you can send a whole block into the message domain, compute it, and get it back as a signal, one block later.
But then, how to do it? Should I be able to pull this out only if I write
a "median~" or [noise_floor~] external?
Or somehow there's another way to do this with some existing external, or a similar technique, or even some audio math trick using [fexpr~] or something?
I don't think you can do any reasonable sort using [fexpr~]... except perhaps a strange undecipherable network of a hundred [fexpr~] or so. I think it's easier to write an external.
This has to do with the other post I did about a project that attempts to
isolate notes into a chord in a spectrum, something like melodyne is does.
So, why is a mean (average) not good enough, while a median would be good enough ? It's possible, but I'd like to hear an explanation.
______________________________**______________________________** __________ | Mathieu BOUCHARD ----- téléphone : +1.514.383.3801 ----- Montréal, QC
Hi Alexandre, maybe the libsms integration into Pd is of use for you - it calculates a model of sinusoidals + residual noise, the latter representing a kind of "noise floor". Those components can then also be modified and resynthesized. http://mtg.upf.edu/static/libsms/
bests, gr~~~
2011/12/21 Alexandre Torres Porres porres@gmail.com:
Hi there, this is a technique for calculating the noise floor of a spectrum, and extracting the peaks.
It'd be used pretty much like I04.Noie Gate Miller's example, that has the "mask" table with a constant multiplier. We'd have instead this "noise-floor" block of audio, also multiplied by a constant.
To get the noise floor, we take the magnitude (or power) spectrum and get the median of small bits of it, like every 32 samples. So the values of every 32 samples would be the median of that section...
this is where I got this from, check page 4 and 5 http://homepages.cae.wisc.edu/~sethares/software/SpectralTools.pdf
this would be kinda like using the [median] or [median_n] objects, but over audio blocks and not number lists.
Since there's the need of calculating this in and using the result back in the same block round into the audio chain, I can't put the spectrum into a table, and then calculate the median over bits of it.
But then, how to do it? Should I be able to pull this out only if I write a "median~" or [noise_floor~] external?
Or somehow there's another way to do this with some existing external, or a similar technique, or even some audio math trick using [fexpr~] or something?
This has to do with the other post I did about a project that attempts to isolate notes into a chord in a spectrum, something like melodyne is does.
thanks Alex
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