Chord Recognition in Music Using a Robust Pitch Class Profile (PCP) Feature and Support Vector Machines (SVM)

Authors

  • Suwatchai Kamonsantiroj Department of Computer and Information Science, King Mongkut's University of Technology, Thailand
  • Lita Wannatrong Department of Computer and Information Science, King Mongkut's University of Technology, Thailand
  • Luepol Pipanmaekaporn King Mongkut's University of Technology North Bangkok, Bangkok, Thailand

DOI:

https://doi.org/10.47738/ijiis.v7i1.191

Keywords:

Robustness, PCP Feature, SVM, Music Chord

Abstract

Music is the most direct and effective means to express emotion, and the effective identification of music works can help us better understand the works and realize the correct interpretation of music. This paper takes robust PCP feature and SVM as the research object. Firstly, the related concepts of terms and a large number of robust CFO description chord spectrum methods used in audio analysis are introduced. Secondly, it expounds the correlation between SVM and speech tonality, designs the system of music chord recognition, tests the performance of the system, and focuses on the test in the direction of recognition rate. Finally, the test results show that the system greatly improves the recognition of music chords with the support of robustness feature optimization and SVM pattern.

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Published

2024-01-07

Issue

Vol. 7 No. 1: January 2024

Section

Articles

License

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