The project is developing a music search engine based on identifying aesthetic similarities. This engine is utilizing power-law metrics to extract statistical proportions of music-theoretic and other attributes of music pieces (e.g., Pitch, Duration, Pitch Distance, Duration Distance, Melodic Intervals, Harmonic Intervals, Melodic Bigrams, etc.). The engine searches for pieces that are aesthetically similar to the input piece using a mean squared error (MSE) approach. Preliminary testing has been done using the Classical Music Archives corpus (14,695 MIDI pieces), combined with 500+ MIDI pieces from other styles (e.g. Jazz, Rock, Country, etc.). A first year effort has demonstrated functionality for additional file formats, including MP3, the predominant format used in web-based music corpora. Assessment and validation experiments will be continued to compare to computational findings indicating aesthetic similarity of retrieved pieces. This research is potentially transformative to the internet music economy and functionality.
