Title :
Speeh/music classification by using statistical neural networks
Author :
Bolat, Bülent ; Küçük, Üna1
Author_Institution :
Yildiz Teknik Universitesi, Istanbul, Turkey
Abstract :
This paper represents a framework for speech/music classification by using statistical neural networks. Zero crossing rate, root mean square power and spectral centroid were used as features. A dataset including 150 audio instances was labeled manually and 105 of them were used to train different networks, which are the probabilistic neural network (PNN), the generalised regression neural network (GRNN) and the radial basis functions (RBF). The remainder of the dataset was used as test item. Training and test performance of these three network types were discussed.
Keywords :
learning (artificial intelligence); music; radial basis function networks; regression analysis; signal classification; spectral analysis; speech processing; GRNN; PNN; RBF; generalised regression neural network; neural network training; probabilistic neural network; radial basis functions; root mean square power; spectral centroid; speech/music classification; statistical neural networks; zero crossing rate; Cepstral analysis; Discrete Fourier transforms; Gaussian processes; Multiple signal classification; Neural networks; Performance evaluation; Root mean square; Testing;
Conference_Titel :
Signal Processing and Communications Applications Conference, 2004. Proceedings of the IEEE 12th
Print_ISBN :
0-7803-8318-4
DOI :
10.1109/SIU.2004.1338300