Feature extraction for sound source material recognition with impact sounds  

作　　者：LIANG Yong CHEN Ke'an ZHANG Bingrui 

机构地区：[1]Department of Environmental Engineering,School of Marine Science and Technology,Northwestern Polytechnical University

出　　处：《Chinese Journal of Acoustics》2017年第2期167-179,共13页声学学报（英文版）

基　　金：supported by the National Natural Science Foundation of China(11074202,11574249)

摘　　要：Sound source recognition is a part of environmental sound recognition,which is one of the most important research areas in pattern recognition.Impact sounds carry much physical information associated with the sound sources,which makes impact sound based sound source recognition an important approach to improve recognition performance.In this study,the impact sound continuum synthesized with a ball-plate collision model is used for material recognition of the impacted plates.The basis function learning method and time-frequency representation methods,including the short time Fourier transform and the wavelet packet transform,are applied into classification and the recognition results are compared.The result shows that the features obtained by using the basis function learning perform better for material classification of the impacted plates than that by using the short time Fourier transform and the wavelet packet transform.This demonstrates the high efficiency and superiority of this method in material recognition of sound sources.Sound source recognition is a part of environmental sound recognition,which is one of the most important research areas in pattern recognition.Impact sounds carry much physical information associated with the sound sources,which makes impact sound based sound source recognition an important approach to improve recognition performance.In this study,the impact sound continuum synthesized with a ball-plate collision model is used for material recognition of the impacted plates.The basis function learning method and time-frequency representation methods,including the short time Fourier transform and the wavelet packet transform,are applied into classification and the recognition results are compared.The result shows that the features obtained by using the basis function learning perform better for material classification of the impacted plates than that by using the short time Fourier transform and the wavelet packet transform.This demonstrates the high efficiency and superiority of this method in material recognition of sound sources.

关 键 词：wavelet impacted collision superiority packet classroom capture stationary bases ordinary 

分 类 号：TN912.34[电子电信—通信与信息系统]