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Erschienen in:
2007 | OriginalPaper | Buchkapitel
Classifying Polyphonic Melodies by Chord Estimation Based on Hidden Markov Model
verfasst von : Yukiteru Yoshihara, Takao Miura, Isamu Shioya
Erschienen in: Intelligent Data Engineering and Automated Learning - IDEAL 2007
Verlag: Springer Berlin Heidelberg
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In this investigation we propose a novel approach for classifying polyphonic melodies. Our main idea comes from for automatic classification of polyphonic melodies by
Hidden Markov model
where the states correspond to well-tempered chords over the music and the observation sequences to some feature values called
pitch spectrum
. The similarity among harmonies can be considered by means of the features and well-tempered chords. We show the effectiveness and the usefulness of the approach by some experimental results.