An Independent Component Analysis Approach to Automatic Music Transcription
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.
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