Research of Chord Recognition based on MPCP

Author

Feng, Wang ; Zhang, Xue-ying ; Li, Bing-nan

Author_Institution

Coll. of Inf. Eng., Taiyuan Univ. of Technol., Taiyuan, China

Volume

4

fYear

2010

fDate

26-28 Feb. 2010

Firstpage

76

Lastpage

79

Abstract

In this paper, five different methods in music recognition are discussed, a new character MPCP is proposed in Chord Recognition. The new character overcome the limitation of the traditional PCP and MFCC, apply for recognition system by combining both characteristics. For features we use MPCP vectors, it is trained by HMM, estimated parameters by Baum-Welch algorithm, finally we acquired accurate chords by Viterbi. The experiment show that the new character perform over than PCP and MFCC for Chord Recognition.

Keywords

acoustic signal processing; hidden Markov models; music; Baum-Welch algorithm; chord recognition; hidden Markov model; mel frequency cepstrum coefficient; music recognition system; Cepstrum; Character recognition; Educational institutions; Frequency conversion; Hidden Markov models; Investments; Mel frequency cepstral coefficient; Parameter estimation; Text recognition; Viterbi algorithm; Hidden Markov Model(HMM); Mel Frequency Cepstrum Coefficient (MFCC); Mel PCP; Pitch class Profile(PCP); chord recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Automation Engineering (ICCAE), 2010 The 2nd International Conference on

Conference_Location

Singapore

Print_ISBN

978-1-4244-5585-0

Electronic_ISBN

978-1-4244-5586-7

Type

conf

DOI

10.1109/ICCAE.2010.5451773

Filename

5451773