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First of all, thank you for providing access to such a great library!
I am trying to implement the calculation of psychoacoustics metrics in my sound classification machine learning project.
I want to calculate a few metrics on short snapshots of sound and as I have many sound events, it leads to a huge number of snapshots.
I noticed the calculation of roughness is significantly greater than other metrics such as loudness or sharpness. I don't know a lot about psychoacoustics or how the calculations are done.
Calculating roughness on a single short 200ms signal (=1 frame) takes around 0.5s.
Calculating roughness directly from the spectrum of this single short 200ms signal takes around 2.1s.
So my questions are:
Has the roughness_dw calculation script been optimized to its full potential?
What can explain the difference in time it takes between calculating from the time signal or the spectrum directly? I would expect the former to take less time, not more.
Many thanks
Cheers
Antoine
The text was updated successfully, but these errors were encountered:
Thanks for raising this point. There is indeed a performance problem with the roughness_dw calculation.
We'll run some tests and try to figure out where the difference between the 2 functions comes from.
If you have any idea about how to improve the code, don't hesitate to share ;)
Hi folks,
First of all, thank you for providing access to such a great library!
I am trying to implement the calculation of psychoacoustics metrics in my sound classification machine learning project.
I want to calculate a few metrics on short snapshots of sound and as I have many sound events, it leads to a huge number of snapshots.
I noticed the calculation of roughness is significantly greater than other metrics such as loudness or sharpness. I don't know a lot about psychoacoustics or how the calculations are done.
Calculating roughness on a single short 200ms signal (=1 frame) takes around 0.5s.
Calculating roughness directly from the spectrum of this single short 200ms signal takes around 2.1s.
So my questions are:
Many thanks
Cheers
Antoine
The text was updated successfully, but these errors were encountered: