Time-frequency audio feature extraction based on tensor representation of sparse coding

被引：7
|
作者：
Zhang, Xue-Yuan [1 ]
He, Qian-Hua [1 ]
机构：
[1] S China Univ Technol, Sch Elect & Informat Engn, Guangzhou 510641, Guangdong, Peoples R China
来源：
ELECTRONICS LETTERS | 2015年 / 51卷 / 02期
关键词：
feature extraction; audio coding; tensor representation; time frequency audio feature extraction scheme; frequency time scale tensor; Gabor dictionary; transient time frequency components; Gabor atoms; tensor element values; sound effects classification; sparse coding features; CLASSIFICATION;
D O I：
10.1049/el.2014.3333
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
A time-frequency audio feature extraction scheme is proposed, in which features are decomposed from a frequency-time-scale tensor. The tensor, derived from a weight vector and a Gabor dictionary in sparse coding, represents the frequency, time centre and scale of transient time-frequency components with different dimensions. The distinguishing Gabor atoms are represented by individual tensor elements, and their associated coding weights are represented by tensor element values. The experimental results of sound effects classification showed performance improvement against that of sparse coding features.
引用
收藏
页码：131 / U20
页数：2
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