Piano Evaluation for Level Normalisation¶

Lack of normalisation for Vamp plugin inputs is a problem when analysing quiet recordings (see #1028).

Testing using a small set of piano recordings, quickly evaluating performance across the first 30 seconds under a number of different normalisation / level management regimes.

Input files¶

Filename	Signal max approx
31.wav	0.57
MAPS_MUS-bach_846_AkPnBcht.wav	0.12
MAPS_MUS-chpn_op7_1_ENSTDkAm.wav	0.33
MAPS_MUS-scn15_7_SptkBGAm.wav	0.13
mz_333_1MINp_align.wav	0.10

The plugin has one internal threshold parameter, which can be lowered to find quieter notes (at the expense of course of more false positives). We don't really want to expose this (or any continuous controls) as a parameter. But we need to have approximately predictable input levels, for this threshold to be meaningful.

Methods¶

Name	Hg revision	Description
norm	d721a17f3e14	Normalise to 0.50 max before running plugin (can't do this in plugin, it's the reference case)
as-is	d721a17f3e14	No normalisation
to-date	d9b688700819	Track max signal level so far, adjust each sample so that max is at 0.50

Results¶

Reporting only the note onset F-measure for the first 30 seconds of each piece.

Filename	norm	as-is	to-date
31.wav	50	33	40
MAPS_MUS-bach_846_AkPnBcht.wav	87	15	62
MAPS_MUS-chpn_op7_1_ENSTDkAm.wav	33	31	31
MAPS_MUS-scn15_7_SptkBGAm.wav	73	16	61
mz_333_1MINp_align.wav	66	3	58

The precision (proportion of correct onsets among detected onsets, or 1 minus the false-positive rate) and recall (proportion of correctly-detected onsets among all ground-truth onsets, or true-positive rate) vary as you would hope:

• when the resulting audio level is quieter than the norm case, precision is high and recall is low but the F-measure is worse than the norm case
• when the resulting audio level is louder than the norm case, precision is low and recall is high and the F-measure is still worse than the norm case

This suggests that our threshold (which happens to be 6) is moderately well-suited to the norm case, at least to optimise F-measure (this might not be the most perceptually useful measure though).

For different piano template sets¶

The above results are all generated using four piano templates, numbered 1-3 plus pianorwc.

Here are results using the norm and as-is methods, but with different sets of piano templates: first with three templates (1-3) and then with each template in turn as the only one.

The template turns out not to make an enormous difference -- perhaps because these recordings contain nothing but piano?

Filename	norm/all	as-is/all	norm/3of4	as-is/3of4	norm/1	as-is/1	norm/2	as-is/2	norm/3	as-is/3	norm/rwc	as-is/rwc
31.wav	50	33	51	30	50	34	44	42	50	32
MAPS_MUS-bach_846_AkPnBcht.wav	87	15	86	16	86	24	75	20	73	10
MAPS_MUS-chpn_op7_1_ENSTDkAm.wav	33	31	32	32	31	22	29	31	35	34
MAPS_MUS-scn15_7_SptkBGAm.wav	73	16	71	19	71	12	68	14	72	17
mz_333_1MINp_align.wav	66	3	68	1	63	4	67	2	67	1

For "generic" template set¶

The above results all use template sets with only piano templates in them.

Here are results using the norm and as-is methods, but with the full set of instrument templates (four pianos plus all the rest).