IPEM and the psychology of electronic music

I'm working with the IPEM Toolbox. A difficult task given that it's tied to Matlab versions 5.3.1 and 6.0. The source code is available and can be toyed with to try to make it compatible with later versions. A fix is to find the original versions, more as a time saving exercise! But as an aside, the concept of IPEM and the extraction of perceptual features is of interest to my own research. And in particular, being an electronic music fan, this article discusses the "Psychology of Electronic Music".

4475 separted notes

I separated the notes from the majority of the IOWA musical instrument samples. Total notes = 4475. WOW! It wasn't easy! I'll be writing about how I did it in my next publication. Look out a few short lines describing about 9 day's of hard work!!

Another Instrument ID paper

I came across another paper on musical instrument ID today:

Loughran,R., Walker,J., O'Neill, M., O'Farrell, M., 2008 - Musical Instrument Identification Using Principal Component Analysis and Multi-Layered Perceptrons.pdf

Loughran, R. uses the temporal envelope of the signal residual (post removal of the RMS temporal envelope) as a feature which I haven't come across before in the literature.

"Temporal and spectral envelopes. The temporal envelope was found by calculating the RMS energy envelope of each sound, which was then filtered using a 3rd order low pass Butterworth filter. This envelope was calculated over the length of each note and so includes temporal information on how the energy within the sound changes over time. Thus this envelope incorporates information regarding the attack time which has been shown to be of high importance to instrument classification [13]. The temporal envelope was then subtracted from the original sound to find the residual. The temporal residual envelope was calculated from the RMS of this residual.