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

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...

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Vydáno v:Electronics letters Ročník 51; číslo 2; s. 131 - 132
Hlavní autoři: Zhang, Xue-Yuan, He, Qian-Hua
Médium: Journal Article
Jazyk:angličtina
Vydáno: The Institution of Engineering and Technology 22.01.2015
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ISSN:0013-5194, 1350-911X, 1350-911X
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Shrnutí: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.
Bibliografie:ObjectType-Article-1
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content type line 23
ISSN:0013-5194
1350-911X
1350-911X
DOI:10.1049/el.2014.3333