Institute of Electrical and Electronics Engineers Inc.;New York: IEEE
摘要:
摘要： This work presents a novel feature extraction approach called nonuniform scale-frequency map for environmental sound classification in home automation. For each audio frame, important atoms from the Gabor dictionary are selected by using the Matching Pursuit algorithm. After the system disregards phase and position information, the scale and frequency of the atoms are extracted to construct a scale-frequency map. Principal Component Analysis (PCA) and Linear Discriminate Analysis (LDA) are then applied to the scale-frequency map, subsequently generating the proposed feature. During the classification phase, a segment-level multiclass Support Vector Machine (SVM) is operated. Experiments on a 17-class sound database indicate that the proposed approach can achieve an accuracy rate of 86.21%. Furthermore, a comparison reveals that the proposed approach is superior to the other time-frequency methods. 其他題名： TASE 出版者： New York: IEEE 出版日期： 2014-04-01 出處： IEEE transactions on automation science and engineering, 2014-04, Vol.11 (2), p.607-613 資源來源： IEEE Electronic Library (IEL) 版權： Copyright The Institute of Electrical and Electronics Engineers, Inc. (IEEE) Apr 2014 識別號： ISSN: 1545-5955 識別號： EISSN: 1558-3783 識別號： DOI: 10.1109/TASE.2013.2285131 識別號： CODEN: ITASC7
