GA-based approach to pitch recognition of musical consonance

Masanori Natsui, Shunichi Kubo, Yoshiaki Tadokoro

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This chapter presents a novel method for the pitch recognition of the musical consonance (i.e., unison or octave) using genetic algorithm (GA). GA is a kind of optimization techniques based on natural selection and genetics. In our method, the pitch recognition is performed by the following two-step procedure: (i) search space reduction using comb filter estimation, and (ii) evolutionary parameter estimation of tone parameters such as notes and volumes by minimizing error between a target waveform and a synthesized waveform using sound templates with estimated parameters. The potential capability of the system is demonstrated through the pitch estimation of randomly-generated consonances. Experimental results show that the system can successfully estimate chords with more than 84% success rate for two-note consonances, and more than 71% success rate for three-note consonances.

Original languageEnglish
Title of host publicationInformatics in Control Automation and Robotics
Subtitle of host publicationSelected Papers from the International Conference on Informatics in Control Automation and Robotics 2006
Pages327-338
Number of pages12
DOIs
Publication statusPublished - 2008 Jun 20
Externally publishedYes

Publication series

NameLecture Notes in Electrical Engineering
Volume15
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Keywords

  • Genetic algorithm
  • Musical consonance
  • Pitch recognition
  • Template matching

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering

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  • Cite this

    Natsui, M., Kubo, S., & Tadokoro, Y. (2008). GA-based approach to pitch recognition of musical consonance. In Informatics in Control Automation and Robotics: Selected Papers from the International Conference on Informatics in Control Automation and Robotics 2006 (pp. 327-338). (Lecture Notes in Electrical Engineering; Vol. 15). https://doi.org/10.1007/978-3-540-79142-3_25