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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Bibliographic Details
Published in:	IEEE/ACM transactions on audio, speech, and language processing Vol. 24; no. 11; pp. 2158 - 2170
Main Authors:	Ping-Keng Jao, Li Su, Yi-Hsuan Yang, Wohlberg, Brendt
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 01.11.2016 The Institute of Electrical and Electronics Engineers, Inc. (IEEE) IEEE - ACM
Subjects:	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
Online Access:	Get full text
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