Thanks for your answer, it's much apreciated.
My goal is to resynthesize arbitary noises. If you do that with
wavetables you end up with a pitch of 20 Hz, hence the FFT.
My product idea was rubbish though and your post confirms that.
For your interest, I recently invented "noisetable synthesis" - take any
sound, randomzie the phases or
circularly convolve with a long chunk of white noise, you get a long
seemless loop of arbitrary spectra.
Good for synthetic cymbals and the like. Take any sound and stretch it
into an endless loop.
Nice for ambient music, too.
But back to my question, I am serious, could you compress a spectrum by
just adding the
bins that fall together? In my understanding, yes, but I am totally not
sure.
My "understanding" might be totally wrong.
Am 31.10.2018 um 03:14 schrieb robert bristow-johnson:
---------------------------- Original Message ----------------------------
Subject: [music-dsp] two fundamental questions Re: FFT for realtime
synthesis?
From: "gm" <[email protected]>
Date: Tue, October 30, 2018 8:17 pm
To: [email protected]
--------------------------------------------------------------------------
>
>
> Am 30.10.2018 um 16:30 schrieb gm:
>> -Compress the peaks (without the surrounding regions) and noise into
>> smaller spectra.
>> (but how? - can you simply add those that fall into the same bins?)
> snip...
>> I am curious about the spectrum compression part, would this work and
>> if not why not?
>
>
> That's a very fundamental DSP question and I am surprised no one
wants to
> answer.
> Probably either no one did read the post or it was too stupid.
>
> My layman's answer is YES OF COURSE, WHAT ARE YOU THINKING but what do I
> know, I am all self taught
> and even taught myself how to read and write (not kidding) so I am
not sure.
mr. g,
i am not exactly "self-taught". i learned my essential math and
electrical engineering in a university setting. but most of these
audio techniques are things i have learned since skool and are mostly
self-taught.
perhaps a quarter century ago i saw a paper about doing something like
real-time additive synthesis by use of the inverse FFT, and while i
don't remember the details, i remember thinking to myself that it
would be very difficult doing synthesis with an iFFT for several
reasons. if the FFT is too small (like N=2048) the frequency
resolution for each bin is crappy for notes below, say, middle C. if
you're not just plopping a "lobe" of template data down onto the iFFT
buffer, then you have to find some way to interpolate to move it's
position a fraction of a bin. if your FFT is too large, you have a
long time to wait between MIDI NoteOn going in and sound coming out.
but a big iFFT is what you need for decent frequency resolution at the
lower pitches.
if you're synthesizing notes that have harmonic partials, then a
periodic or quasi-periodic synthesis technique in the time-domain is
likely your simplest bet. i am a partisan of Wavetable Synthesis
because, with the one restriction that the partials are nearly or
perfectly harmonic, wavetable synthesis is general. nearly any
existing acoustic instrument can be convincingly synthesized with
wavetable synthesis. as long as you have a good pitch detector, it's
not hard to analyze a given note and break it into wavetables. but
you need to know the period (to a sub-sample precision) and you need
to be able to interpolate convincingly between samples. BOTH in the
analysis phase and in the synthesis phase. wavetable synthesis works
well for notes with an attack (what you might use a sampling and
looping "synthesizer" to do), additive synthesis (as long as the
partials are nearly harmonic), classic waveforms (like saw, square,
PWM, sync-saw, sync-square) and you can cross-fade (or "interpolate")
between wavetables to get the ability to change the sound. you need a
good tracking pitch detector in the analysis phase.
but, for fun, there are other synthesis techniques from the olden
days. Classic Subtractive synthesis, Karplus-Strong, Physical
Modeling, Non-linear Waveshaping, Geometric Summation formula, IIR
impulse response, comb-filter impulse response, "FOF" (something like
overlapping wavelets or grains). but they're all time domain.
--
r b-j [email protected]
"Imagination is more important than knowledge."
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