Title :
Multi-timbre chord classification using wavelet transform and self-organized map neural networks
Author :
Su, Borching ; Jeng, Shyh-Kang
Author_Institution :
Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan
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
Keywords :
acoustic signal processing; hearing; music; self-organising feature maps; wavelet transforms; cerebra; chords classification; human ears; multi-timbre chord classification; musical chord recognition; musical chords; musical timbres; noisy environment; self-organized map neural networks; wavelet transform; Acoustic noise; Acoustical engineering; Ear; Humans; Music; Neural networks; Timbre; Time frequency analysis; Wavelet transforms; Working environment noise;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 2001. Proceedings. (ICASSP '01). 2001 IEEE International Conference on
Conference_Location :
Salt Lake City, UT
Print_ISBN :
0-7803-7041-4
DOI :
10.1109/ICASSP.2001.940383
