Why does the objectionable part of it seem to reduce with oversampling? Does IMD add a lot of higher harmonics which are more likely to result in audible aliasing?I think that's just IMD plus beat frequency (the latter happens even on acoustic instruments cuz it's just interference between two nearing frequencies)
Since I know nothing about how and with which device/software you experienced this, I'll just leave this pic so you can draw your conclusions:Why does the objectionable part of it seem to reduce with oversampling? Does IMD add a lot of higher harmonics which are more likely to result in audible aliasing?
The weights in a neural network are just filters. The anti-aliasing filter is another filter. You can multiply the weights of those two filters and just store the resulting filter. No extra compute after the model is trained.How do you not add extra compute if you want to bake in an anti-aliasing filter... wouldn't it have to oversample to do so?
The neural network could potentially learn to do anti aliasing without oversampling by virtue of the fact that internally it doesn't have only one signal but instead lots of features (potentially thousands). Whether or not you want to argue that that's effectively oversampling is another matter, but it's certainly already extremely redundant. I think the bigger issue is that ML experts for the most part are not signal processing or audio experts.The input to an amp can easily reach ultrasonic frequencies. The initial pick attack has copious high frequency content.
Many distortion pedals have an output spectrum that reaches far beyond 20kHz.
If you limit the frequency to 10kHz it will sound dull.
None of that really matters though. What matters is the fundamental concept of aliasing which some here don't seem to grasp. Any time you have a nonlinear transfer function you create distortion. In guitar gear the transfer function is usually some sort of clipping behavior. At the limit this turns a sine wave into a square wave. A square wave has harmonics that extend well into the ultrasonic range.
If you don't oversample enough those harmonics alias into the audible spectrum. No amount of hand-waving changes that. The correct thing to do is to increase the sample rate and then downsample after all the processing is done.
BTW @DLC86, the sweep should be 10k-20k with a quick fade-in/out at the ends to prevent a 'pop' in the measurement.
Use this sweep I made:
1Min 10kHz-20kHz Sine Sweep 48kHz, Mono and normalized to -0.1dB with Fade In/Out.Code:https://drive.google.com/file/d/1qM5OrM40K-RfQfm0K3mbPvl-VGMrPmqc
Lower its level in DAW.
My span settings, I click the span window to reset it before hitting play in DAW.
Offset Normalized so I can see the aliasing -dB value on the db scale on the right.
View attachment 5360
Big difference in aliasing with realistic vs unrealistic input dB values at the 10k-20k range.
View attachment 5361
A: Just amp block, no IR.a => should I use just an Amp Block by itself only in Tonex -or- should I also add a Cab / IR Block ?
b => cant see where / how do I adjust the Input DB Values ? - as for example you have in your test to say -10db and -35db ?
Uhh, no.The neural network could potentially learn to do anti aliasing without oversampling
If you want to perform a meaningful test for aliasing - i.e., one that directly identifies audible aliasing artifacts - I described a method for doing so some years ago on a now-disappeared forum. I later described the test on TGP here: Digital Artifacts? Here's a quote of the relevant part:
"Using a DAW, create a sine sweep that goes from ca. 150 Hz to maybe 4k in 4-5 seconds and add harmonics. The application I use allows added harmonics up to fifth.
Apply that signal to the input of your modeler. If it creates aliasing products, from some point mid-sweep, in addition to the ascending pitch, you will hear descending tones. It's not at all a subtle thing. You can clearly hear aliasing that is 50-60dB in level below the fundamental."
Apply the test signal at a similar level to the one produced by your guitar. The test uses the most important instrument for detecting aliasing - your ears - and needs no interpretation. It enables you to clearly hear digital aliasing apart from other noise and distortion products.
Here's a link to the sweep I use for this test: Alias Test. If you're interested, it would be a good idea to download it ASAP, as I won't leave it up indefinitely.
You missed the entire point, then. From my description above: "Apply that signal to the input of your modeler (or plug). If it creates aliasing products, from some point mid-sweep, in addition to the ascending pitch, you will hear descending tones. It's not at all a subtle thing."Not using SPAN Plus or anything else - just listening several times - there was a very clear and very obvious audible difference between the two through my NS10's and Celestion F12-X200 and Matrix GT800 up at loud gig level.
You missed the entire point, then. From my description above: "Apply that signal to the input of your modeler (or plug). If it creates aliasing products, from some point mid-sweep, in addition to the ascending pitch, you will hear descending tones. It's not at all a subtle thing."
I'll clarify: the sweep moves up in frequency. IOW, it begins at a lower pitch and moves to a higher pitch. If the system/plug/block you're evalating creates aliasing products of any consequence, you will hear pitches moving downward, IOW, going from a higher pitch to a lower pitch. Words like "clean," "clear," "smooth," etc., are completely irrelevant. They have no place in the discussion. Either you hear tones moving downward or you do not. In the latter case, there is no aliasing of consequence. In the former, there is aliasing.
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So that's it then, no room for further discussion?absolutely no / zero / none / nada etc...