DocumentCode :
176545
Title :
Onset detection using leared dictionary by K-SVD
Author :
Wenming Gui ; Xi Shao
Author_Institution :
Jinling Inst. of Technol., Nanjing, China
fYear :
2014
fDate :
29-30 Sept. 2014
Firstpage :
406
Lastpage :
409
Abstract :
This paper presents a promising and novel onset detection algorithm. Instead of traditional musical signal processing methods based on orthogonal transform such as Fourier Transform and Wavelet Transform, we focused on sparse representation with learned dictionary by K-SVD. We discussed the theorem and the methods of K-SVD for onset detection. The experimental results indicted that the proposed approach was theoretically feasible and practically effective.
Keywords :
Fourier transforms; audio signal processing; dictionaries; music; signal detection; signal representation; singular value decomposition; wavelet transforms; Fourier transform; K-SVD; learned dictionary; musical audio; musical signal processing methods; onset detection algorithm; orthogonal transform; sparse representation; wavelet transform; Algorithm design and analysis; Dictionaries; Feature extraction; Matching pursuit algorithms; Signal processing algorithms; Transforms; Vectors; K-SVD; analytic dictionary; learned dictionary; note onset detection; sparse representation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Research and Technology in Industry Applications (WARTIA), 2014 IEEE Workshop on
Conference_Location :
Ottawa, ON
Type :
conf
DOI :
10.1109/WARTIA.2014.6976281
Filename :
6976281
Link To Document :
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