o do time scaling. lemme know if that might be helpful.
L8r,
r b-j
------------ Original Message --------------------
Subject: Re: [music-dsp] 2-point DFT Matrix for subbands Re: FFT for
realtime synthesis?
From: &quo
opinion, the most basic phase
vocoder implemented to do time scaling.� lemme know if that might be helpful.
L8r,
r b-j
�
Original Message ----------------
Subject: Re: [music-dsp] 2-point DFT Matrix for subbands Re: FFT for realtime
synthesis?
From: "gm&
--------------
Subject: Re: [music-dsp] 2-point DFT Matrix for subbands Re: FFT for
realtime synthesis?
From: "gm"
Date: Fri, November 9, 2018 4:19 pm
To: music-dsp@music.columbia.edu
--
>
> hm, my applica
- Original Message
Subject: Re: [music-dsp] 2-point DFT Matrix for subbands Re: FFT for realtime
synthesis?
From: "gm"
Date: Fri, November 9, 2018 4:19 pm
To: music-dsp@music.columbia.edu
---
y, but i credited both the DIT and DIF FFT
to Cooley and Tukey. that might be an incorrect
historical impression.
-------- Original Message
----
Subject: Re: [music-dsp]
ecutive" DFTs of the raw input data and combine them into a longer
>>>> DFT.
>>>>
>>>> (And I don't know anything about the historical question!)
>>>>
>>>> -Ethan
>>>>
>>>>
>>>>
>>>> On Mon, Nov 5,
Tukey. that might be an incorrect historical impression.
---------------- Original Message
------------
Subject: Re: [music-dsp] 2-point DFT Matrix for
subbands Re: FFT for realtime synthesis?
From: "
gt;>> On Mon, Nov 5, 2018 at 2:18 PM, robert bristow-johnson <
>>> r...@audioimagination.com> wrote:
>>>
>>>>
>>>>
>>>> Ethan, that's just the difference between Decimation-in-Frequency FFT
>>>> and Decimation-in-T
No matter how you go about this, the the Fast Fourier will in almost every case
act as some sort of ensemble measurement over it's length, and maybe do some
filtering between consecutive transform steps. Maybe you even continuously
average in the frequency domain, using per sample sliding FFT fram
Ethan, that's just the difference between Decimation-in-Frequency FFT
>>> and Decimation-in-Time FFT.
>>>
>>> i guess i am not entirely certainly of the history, but i credited both
>>> the DIT and DIF FFT to Cooley and Tukey. that might be an incorrect
>
I think I figured it out.
I use 2^octave * SR/FFTsize -> toERBscale -> * log2(FFTsize)/42 as a
scaling factor for the windows.
Means the window of the top octave is about 367 samples at 44100 SR -
does that seem right?
Sounds better but not so different, still pretty blurry and somewhat
re
Further tests let me assume that you can do it on a log2 scale but that
appropriate window sizes are crucial.
But how to derive these optmal window sizes I am not sure.
I could calculate the bandwitdh of the octave band (or an octave/N band)
in ERB
for instance but then what? How do I derive a
At the moment I am using decreasing window sizes on a log 2 scale.
It's still pretty blurred, and I don't know if I just don't have the
right window parameters,
and if a log 2 scale is too coarse and differs too much from an auditory
scale, or if if I don't have
enough overlaps in resynthesis
On 7/11/2018 12:03 AM, gm wrote:
A similar idea would be to do some basic wavelet transfrom in octaves
for instance and then
do smaller FFTs on the bands to stretch and shift them but I have no idea
if you can do that - if you shift them you exceed their bandlimit I assume?
and if you stretch th
The background of the idea was to get a better time resolution
with shorter FFTs and then to refine the freuqency resolution.
You would think at first glance that you would get the same time resolution
as you would with the longer FFT, but I am not sure, if you do overlaps
you get kind of a sli
>
>>>
>>> Ethan, that's just the difference between Decimation-in-Frequency FFT
>>> and Decimation-in-Time FFT.
>>>
>>> i guess i am not entirely certainly of the history, but i credited both
>>> the DIT and DIF FFT to Cooley and Tukey. t
e history, but i credited both
>> the DIT and DIF FFT to Cooley and Tukey. that might be an incorrect
>> historical impression.
>>
>>
>>
>> ---- Original Message
>> Subject: Re: [music-d
ic.columbia.edu
Subject: Re: [music-dsp] 2-point DFT Matrix for subbands Re: FFT for realtime
synthesis?
I don't think that's correct -- DIF involves first doing a single stage of
butterfly operations over the input, and then doing two smaller DFTs on that
preprocessed data. I don't
and
> Decimation-in-Time FFT.
>
> i guess i am not entirely certainly of the history, but i credited both
> the DIT and DIF FFT to Cooley and Tukey. that might be an incorrect
> historical impression.
>
>
>
> ---------------- Original Message --------------
ssion.
Original Message
Subject: Re: [music-dsp] 2-point DFT Matrix for subbands Re: FFT for realtime
synthesis?
From: "Ethan Fenn"
Date: Mon, November 5, 2018 10:17 am
To: music-dsp@mus
Am 05.11.2018 um 16:17 schrieb Ethan Fenn:
Of course it's possible you'll be able to come up with a clever
frequency estimator using this information. I'm just saying it won't
be exact in the way Cooley-Tukey is.
Maybe, but not the way I laid it out.
Also it seems wiser to interpolate sp
It's not exactly Cooley-Tukey. In Cooley-Tukey you take two _interleaved_
DFT's (that is, the DFT of the even-numbered samples and the DFT of the
odd-numbered samples) and combine them into one longer DFT. But here you're
talking about taking two _consecutive_ DFT's. I don't think there's any
cheap
Am 05.11.2018 um 01:56 schrieb gm:
so you do the "radix 2 algorithm" if you will on a subband, and now what?
the bandlimits are what? the neighbouring upper and lower bands?
how do I get a frequency estimate "in between" out of these two real
values that describe the upper and lower limit of
Am 05.11.2018 um 01:39 schrieb robert bristow-johnson:
mr. g,
I think what you're describing is the Cooley-Tukey Radix-2 FFT algorithm.
yes that seems kind of right, though I am not describing something but
posting a question actually
and the "other thing" was an answer to a question
may
and the other thing you're describing is what they usually call "sinusoidal
modeling.".--r b-j r...@audioimagination.com"Imagination is
more important than knowledge."
Original message
From: gm
Date: 11/4/2018 4:14 PM (GMT-08:00)
To: music-dsp@mus
mr. g,I think what you're describing is the Cooley-Tukey Radix-2 FFT
algorithm.--r b-j r...@audioimagination.com"Imagination is
more important than knowledge."
Original message
From: gm
Date: 11/4/2018 4:14 PM (GMT-08:00)
To: music-dsp@music.colum
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