Multi-timbre chord classification using wavelet transform and self-organized map neural networks

Authors:
Borching Su;Shyh-Kang Jeng
Affiliations:
Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan;-
Venue:
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 2001. on IEEE International Conference - Volume 05
Year:
2001

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Cited 1

Automatic Chord Estimation from Audio: A Review of the State of the Art

IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)

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Abstract

This paper presents a new method for musical chord recognition based on a model of human perception. We classify the chords directly from the sound without the information of timbres and notes. A wavelet-based transform as well as a self-organized map (SOM) neural network is adopted to imitate human ears and cerebra, respectively. The resultant system can classify chords very well even in a noisy environment.