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The search for a flexible and concise alternate representation for digital musical sound leads to the proposal for the use of the MIDI (Musical Instrument Digital Interface) protocol. The problem becomes one of automating the conversion process from sound to MIDI. This requires processing musical sound and extracting the information necessary to represent the sound as MIDI data. We have conducted studies which have led to algorithms for segmentation of the sound and pitch detection of the individual notes. We describe a novel method for pitch detection using subset selection with dictionaries containing harmonic spectra from samples of musical sounds. Examples demonstrating applicability to monophonic sounds as well as signals with multiple sound sources are given, including detection of objects in a complex background scene.