We used Independent Component Analysis (ICA) with sparse coding to analyze music spectral sequences. We modelled an audio spectrum as an approximate mixture of the spectra of individual notes, using our ICA approach to 'unmix' this to find the individual notes and note spectra. Notes are assumed to be approximately independent, and sparse (mostly off). Results on synthesized harpsichord music are encouraging, producing an approximate piano-roll transcription, and a passable rendition of the original music when resynthesized. We are currently working to extend and improve this through the use of temporal information of note activities and to handle more complex timbral behaviour.
https://www.aes.org/e-lib/browse.cfm?elib=12558
Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!
This paper costs $33 for non-members and is free for AES members and E-Library subscribers.
Learn more about the AES E-Library
Start a discussion about this paper!