Classifying polyphonic melodies by chord estimation based on hidden Markov model

Authors:
Yukiteru Yoshihara;Takao Miura;Isamu Shioya
Affiliations:
Dept. of Elect.& Elect. Engr., HOSEI University, Tokyo, Japan;Dept. of Elect.& Elect. Engr., HOSEI University, Tokyo, Japan;Dept. of Elect.& Elect. Engr., HOSEI University, Tokyo, Japan
Venue:
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
Year:
2007

Citing 6
Cited 0

Manipulation of music for melody matching

MULTIMEDIA '98 Proceedings of the sixth ACM international conference on Multimedia
Information Retrieval: Algorithms and Heuristics

Information Retrieval: Algorithms and Heuristics
Harmonic models for polyphonic music retrieval

Proceedings of the eleventh international conference on Information and knowledge management
Similarity among melodies for music information retrieval

CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Melody Classification Using EM Algorithm

COMPSAC '05 Proceedings of the 29th Annual International Computer Software and Applications Conference - Volume 01
Classifying polyphony music based on markov model

IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning

Quantified Score

Hi-index	0.00

Visualization

Abstract

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.