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 window length from that for that band?

I understand that bandwitdh is inversly proportional to window length.

So it seems very easy actually but I am stuck here...


Am 06.11.2018 um 16:13 schrieb gm:
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 (I have four).
Or if it's all together.

The problem is the lowest octave or the lowest two octaves, where I need a long window for frequency estimation and partial tracking, it just soundded bad when the window was smaller in this range
because the frequencies are blurred too much I assume.

Unfortunately I am not sure what quality can be achieved and where the limits are with this approach.


Am 06.11.2018 um 14:20 schrieb Ross Bencina:
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 them I am not sure what happens, you shift their frequency content down I assume? Its a little bit fuzzy to me what the waveform in a such a band represents
and what happens when you manipulate it, or how you do that.

Look into constant-Q and bounded-Q transforms.

Ross.
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