TY - GEN
T1 - Automatic chord recognition based on probabilistic integration of acoustic features, bass sounds, and chord transition
AU - Itoyama, Katsutoshi
AU - Ogata, Tetsuya
AU - Okuno, Hiroshi G.
PY - 2012
Y1 - 2012
N2 - We have developed a method that identifies musical chords in polyphonic musical signals. As musical chords mainly represent the harmony of music and are related to other musical elements such as melody and rhythm, we should be able to recognize chords more effectively if this interrelationship is taken into consideration. We use bass pitches as clues for improving chord recognition. The proposed chord recognition system is constructed based on Viterbi-algorithm- based maximum a posteriori estimation that uses a posterior probability based on chord features, chord transition patterns, and bass pitch distributions. Experimental results with 150 Beatles songs that has keys and no modulation showed that the recognition rate was 73.7% on average.
AB - We have developed a method that identifies musical chords in polyphonic musical signals. As musical chords mainly represent the harmony of music and are related to other musical elements such as melody and rhythm, we should be able to recognize chords more effectively if this interrelationship is taken into consideration. We use bass pitches as clues for improving chord recognition. The proposed chord recognition system is constructed based on Viterbi-algorithm- based maximum a posteriori estimation that uses a posterior probability based on chord features, chord transition patterns, and bass pitch distributions. Experimental results with 150 Beatles songs that has keys and no modulation showed that the recognition rate was 73.7% on average.
UR - http://www.scopus.com/inward/record.url?scp=84864350748&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84864350748&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-31087-4_7
DO - 10.1007/978-3-642-31087-4_7
M3 - Conference contribution
AN - SCOPUS:84864350748
SN - 9783642310867
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 58
EP - 67
BT - Advanced Research in Applied Artificial Intelligence - 25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2012, Proceedings
T2 - 25th International Conference on Industrial Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2012
Y2 - 9 June 2012 through 12 June 2012
ER -