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A SYSTEM FOR ACOUSTIC CHORD TRANSCRIPTION AND KEY EXTRACTION FROM AUDIO USING HIDDEN MARKOV MODELS TRAINED ON SYNTHESIZED AUDIO A DISSERTATION SUBMITTED TO THE DEPARTMENT OF MUSIC AND THE COMMITTEE ON GRADUATE STUDIES OF STANFORD UNIVERSITY IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY Kyogu Lee March 2008 c Copyright by Kyogu Lee 2008 All Rights Reserved ii I certify that I have read this dissertation and that in my opinion it is fully adequate in scope and quality as a dissertation for the degree of Doctor of Philosophy Julius Smith III Principal Adviser I certify that I have read this dissertation and that in my opinion it is fully adequate in scope and quality as a dissertation for the degree of Doctor of Philosophy Jonathan Berger I certify that I have read this dissertation and that in my opinion it is fully adequate in scope and quality as a dissertation for the degree of Doctor of Philosophy Chris Chafe I certify that I have read this dissertation and that in my opinion it is fully adequate in scope and quality as a dissertation for the degree of Doctor of Philosophy Malcolm Slaney Approved for the University Committee on Graduate Studies iii Abstract Extracting high level information of musical attributes such as melody harmony key or rhythm from the raw waveform is a critical process in Music Information Retrieval MIR systems Using one or more of such features in a front end one can efficiently and effectively search retrieve and navigate through a large collection of musical audio Among those musical attributes harmony is a key element in Western tonal music Harmony can be characterized by a set of rules stating how simultaneously sounding or inferred tones create a single entity commonly known as a chord how the elements of adjacent chords interact melodically and how sequences of chords relate to one another in a functional hierarchy Patterns of chord changes over time allow for the delineation of structural features



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