Musical audio analysis using sparse representations

Mark D. Plumbley (), Samer A. Abdallah, Thomas Blumensath, Maria G. Jafari, Andrew Nesbit, Emmanuel Vincent and Beiming Wang
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Mark D. Plumbley: University of London, Centre for Digital Music, Department of Electronic Engineering, Queen Mary
Samer A. Abdallah: University of London, Centre for Digital Music, Department of Electronic Engineering, Queen Mary
Thomas Blumensath: University of London, Centre for Digital Music, Department of Electronic Engineering, Queen Mary
Maria G. Jafari: University of London, Centre for Digital Music, Department of Electronic Engineering, Queen Mary
Andrew Nesbit: University of London, Centre for Digital Music, Department of Electronic Engineering, Queen Mary
Emmanuel Vincent: University of London, Centre for Digital Music, Department of Electronic Engineering, Queen Mary
Beiming Wang: University of London, Centre for Digital Music, Department of Electronic Engineering, Queen Mary

A chapter in Compstat 2006 - Proceedings in Computational Statistics, 2006, pp 105-117 from Springer

Abstract: Abstract Sparse representations are becoming an increasingly useful tool in the analysis of musical audio signals. In this paper we will given an overview of work by ourselves and others in this area, to give a flavour of the work being undertaken, and to give some pointers for further information about this interesting and challenging research topic.

Keywords: Sparse representations; music; audio; independent components analysis; automatic music transcription; non-negative matrix factorization; source separation (search for similar items in EconPapers)
Date: 2006
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-7908-1709-6_9

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DOI: 10.1007/978-3-7908-1709-6_9

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