Monaural Music Source Separation Using Convolutional Sparse Coding

We present a comprehensive performance study of a new time-domain approach for estimating the components of an observed monaural audio mixture. Unlike existing time-frequency approaches that use the product of a set of spectral templates and their corresponding activation patterns to approximate the...

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Vydané v:	IEEE/ACM transactions on audio, speech, and language processing Ročník 24; číslo 11; s. 2158 - 2170
Hlavní autori:	Ping-Keng Jao, Li Su, Yi-Hsuan Yang, Wohlberg, Brendt
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.11.2016 The Institute of Electrical and Electronics Engineers, Inc. (IEEE) IEEE - ACM
Predmet:	Activation Algorithms Approximation Coding Computer Science Convolution Convolutional codes convolutional sparse coding Convolutional sparse coding (CSC) Dictionaries Information Science Instruments Mathematics MATHEMATICS AND COMPUTING Monaural music source separation multipitch estimation (MPE) Music Musical scores non-negative matrix factorization nonnegative matrix factorization (NMF) phase score-informed source separation Separation Sound filters Source separation Time-domain analysis
ISSN:	2329-9290, 2329-9304
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