C4.5: programs for machine learning
C4.5: programs for machine learning
Computational auditory scene analysis
Computational auditory scene analysis
Application of the Bayesian probability network to music scene analysis
Computational auditory scene analysis
Sound ontology for computational auditory scence analysis
AAAI '98/IAAI '98 Proceedings of the fifteenth national/tenth conference on Artificial intelligence/Innovative applications of artificial intelligence
Musical instrument recognition using cepstral coefficients and temporal features
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02
Music genre classification based on ensemble of signals produced by source separation methods
Intelligent Decision Technologies
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To augment communication channels of human-computer interaction, various kinds of sound recognition are required. In particular, musical instrument indentification is one of the primitive functions in obtaining auditory information. The pitch dependency of timbres has not been fully exploited in musical instrument identification. In this paper, we present a method using an F0-dependent multivariate normal distribution of which mean is represented by a cubic polynomial of fundamental frequency (F0). This F0-dependent mean function represents the pitch dependency of each feature, while the F0-normalized covariance represents its non-pitch dependency. Musical instrument sounds are first analyzed by the F0-dependent multivariate normal distribution, and then identified by using the discriminant function based on the Bayes decision rule. Experimental results of identifying 6,247 solo tones of 19 musical instruments by 10-fold cross validation showed that the proposed method improved the recognition rate at individualinstrument level from 75.73% to 79.73%, and the recognition rate at category level from 88.20% to 90.65%. Based on these results, systematic generation of musical sound ontology is investigated by using the C5.0 decision tree program.