TY - GEN
T1 - Recognition of sounds using square cauchy mixture distribution
AU - Ito, Akinori
PY - 2017/3/27
Y1 - 2017/3/27
N2 - In this paper, a new probability density distribution, 'the square Cauchy mixture distribution' is proposed for recognition of sound. The proposed density is based on the Cauchy distribution and modified so that it has mean and variance. Since the proposed density can be calculated using only simple arithmetic operations, it can be calculated faster than the Gaussian mixture model (GMM). In addition to the definition of the proposed distribution, a parameter estimation method based on the gradient descent is also described. Two experiments were conducted such as recognition of environmental sound and recognition of singer of the singing voice. The results of the experiments revealed that the proposed method was 10% to 15% faster than the GMM with addlog operation and the recognition performance was comparable.
AB - In this paper, a new probability density distribution, 'the square Cauchy mixture distribution' is proposed for recognition of sound. The proposed density is based on the Cauchy distribution and modified so that it has mean and variance. Since the proposed density can be calculated using only simple arithmetic operations, it can be calculated faster than the Gaussian mixture model (GMM). In addition to the definition of the proposed distribution, a parameter estimation method based on the gradient descent is also described. Two experiments were conducted such as recognition of environmental sound and recognition of singer of the singing voice. The results of the experiments revealed that the proposed method was 10% to 15% faster than the GMM with addlog operation and the recognition performance was comparable.
KW - Gaussian distribution
KW - addlog
KW - cauchy distribution
KW - environmental sound recognition
KW - singer recognition
KW - squared cauchy distribution
UR - http://www.scopus.com/inward/record.url?scp=85018714138&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85018714138&partnerID=8YFLogxK
U2 - 10.1109/SIPROCESS.2016.7888359
DO - 10.1109/SIPROCESS.2016.7888359
M3 - Conference contribution
AN - SCOPUS:85018714138
T3 - 2016 IEEE International Conference on Signal and Image Processing, ICSIP 2016
SP - 726
EP - 730
BT - 2016 IEEE International Conference on Signal and Image Processing, ICSIP 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE International Conference on Signal and Image Processing, ICSIP 2016
Y2 - 13 August 2016 through 15 August 2016
ER -