reduce pydra overhead

[satra]

in the senselab package which processes audio (mostly through python functions), we are seeing significant pydra overhead. to try and debug a bit of this, i looked at scalene (github.com/plasma-umass/scalene) and it seems like we could incorporate it into the codebase, or use it to optimize bits of it. there is an ai model integration into scalene.

[djarecka]

Thanks Satra, I can take a look after SFN

[wilke0818]

As part of this issue, one of the other maintainers of senselab tried to do some performance testing and found the following when using 535 EMO-DB short clips

Task	With Pydra (s)	Without (s)
Read audios	12.5	0.5
Save audios	10.63	0.2
Downmix to mono	15.0	0.1
Resample	16.0	0.1
OpenSMILE features	33.0	20.0
Praat/parselmouth features	93.7*	246.1
Torchaudio features	37.8	16.2
Audiomentations (gain)	13.5	0.3
Torchaudiomentations (gain)	5.3	0.2

*on Pydra 0.23 it was even faster (~70s)