Hypothetically, how an FFT-based equalizer can be programmed.

One of the concepts which I only recently posted about was, that I had activated an equalizer function, that was once integrated into how the PulseAudio sound server works, but which may be installed with additional packages, in more-recent versions of Debian Linux. As I wrote, to activate this under Debian 8 / Jessie was a bit problematic at first, but could ultimately be accomplished. The following is what the controls of this equalizer look like, on the screen:

Equalizer_1

And, this is what the newly-created ‘sink’ is named, within the (old) KDE-4 desktop manager’s Settings Panel:

Equalizer_2

What struck me as remarkable about this, was its naming, as an “FFT-based Equalizer…”. I had written an earlier posting, about How the Fast Fourier Transform differs from the Discrete Fourier Transform. And, because I tend to think first, about how convolutions may be computed, using a Discrete Cosine Transform, it took me a bit of thought, to comprehend, how an equalizer function could be implemented, based on the FFT.

BTW, That earlier posting which I linked to above, has as a major flaw, a guess on my part about how MP3 sound compression works, that makes a false assumption. I have made more recent postings on how sound-compression schemes work, which no longer make the same false assumption. But otherwise, that old posting still explains, what the difference between the FFT and other, Discrete Transforms is.

So, the question which may go through some readers’ minds, like mine, would be, how a graphic equalizer based on the FFT can be made computationally efficient, to the maximum. Obviously, when the FFT is only being used to analyze a sampling interval, what results is a (small) number of frequency coefficients, spaced approximately uniformly, over a series of octaves. Apparently, such a set of coefficients-as-output, needs to be replaced by one stream each, that isolates one frequency-component. Each stream then needs to be multiplied by an equalizer setting, before being mixed into the combined equalizer output.

I think that one way to compute that would be, to replace the ‘folding’ operation normally used in the Fourier Analysis, with a procedure, that only computes one or more product-sums, of the input signal with reference sine-waves, but in each case except for the lowest frequency, over only a small fraction of the entire buffer, which becomes shorter according to powers of 2.

Thus, it should remain constant that, in order for the equalizer to be able to isolate the frequency of ~31Hz, a sine-product with a buffer of 1408 samples needs to be computed, once per input sample. But beyond that, determining the ~63Hz frequency-component, really only requires that the sine-product be computed, with the most recent 704 samples of the same buffer. Frequency-components that belong to even-higher octaves can all be computed, as per-input-sample sine-products, with the most-recent 352 input-samples, etc. (for multiples of ~125Hz). Eventually, as the frequency-components start to become odd products of an octave, an interval of 176 input samples can be used, for the frequency-components belonging to the same octave, thus yielding the ~500Hz and ~750Hz components… After that, in order to filter out the ~1kHz and the ~1.5kHz components, a section of the buffer only 88 samples long can be used…

Mind you, one alternative to doing all that would be, to apply a convolution of fixed length to the input stream constantly, but to recompute that convolution, by first interpolating frequency-coefficients between the GUI’s slider-positions, and then applying one of the Discrete Cosine Transforms to the resulting set of coefficients. The advantage to using a DCT in this way would be, that the coefficients would only need to be recomputed once, every time the user changes the slider-positions. But then, to name the resulting equalizer an ‘FFT-based’ equalizer, would actually be false.

(Updated 7/25/2020, 11h15… )

Continue reading Hypothetically, how an FFT-based equalizer can be programmed.

Getting the integrated equalizer to work, from Debian Jessie, KDE 4.

I happen to have an older laptop, which I name ‘Klystron’, that is running Debian 8 / Jessie, with KDE 4 as its desktop manager. Don’t ask me why, but I tend to leave older builds of Linux running on some of my computers, just because they seem to be running without any deficiencies.

That laptop has lousy speakers. I decided a few days ago, that it would benefit, if I could get the 14-band graphical equalizer to work, that is generally available on Linux computers which, like that laptop, use the ‘PulseAudio’ sound server. However, on this old version of Linux, achieving that was a bit harder than it’s supposed to be. Yet, because I succeeded, I felt that I should share with the community, what the steps were, needed to succeed.

First of all, this is what the equalizer looks like, which I can now open on that laptop:

Equalizer_1

And it works!

 

In order to get this sort of equalizer working with PulseAudio, eventually, the following two modules need to be loaded:

module-equalizer-sink

module-dbus-protocol

And, if I gave the command ‘load-module…’ naively from the command-line, as user, because under my builds of Linux, PulseAudio runs in user mode, both these modules seem to load fine, without my having to install any additional packages.

On more recent builds of Linux, one needs to install the package ‘pulseaudio-equalizer’ to obtain this feature, or some similarly-named package. But, because these two modules just loaded fine under Debian / Jessie, I guess the functionality once came integrated with PulseAudio.

But I soon started to run in to trouble with these modules, and discovered why, then, the equalizer function was not set up to run out-of-the-box…

(Updated 6/26/2020, 10h30… )

Continue reading Getting the integrated equalizer to work, from Debian Jessie, KDE 4.

Playing Games With Numbering

There is an art-form which seems to exist, in the design of graphical equalizers, to choose channel-frequencies that are approximately spaced one octave apart, yet which will produce numbers that ‘look clean’ in decimal. For example, a sequence of frequencies is possible that goes 150 Hz, 300 Hz, 600 Hz, 1.2 kHz, 2.4 kHz, 5 kHz, 10 kHz, 20 kHz, resulting in an 8-band equalizer. Notably, in this example, 2.4 kHz will be treated as if it was 2.5 kHz as well, so that the next-higher band, at 5 kHz, will seem to be an exact octave higher.

This will not work as well, with a 20-band equalizer.

Dirk

(Edit 03/26/2017 : )

Also, the difference between 2.4 and 2.5 is less than 1/20. Anything further-off will produce a hot-spot. So below 150 Hz, we might be ill-advised to put 80 instead of 75, because they would be too close by more than 1/20. I would actually suggest, 76 – 38 – 20 . Mind you, that 20 Hz suggestion would be off by 1/19, but who hears those frequencies so accurately anyway? ;)