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Musical Source Separation: A Review of Techniques and the Proposal of Cepstromarg Filtering

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Overview

Year:
2019
Contributor:
Charous, Aaron (creator)
Sandstede, Björn (thesis advisor)
Rose, Christopher (reader)
Brown University. Applied Mathematics (sponsor)
Genre:
theses
Subject:
Information storage and retrieval systems--Music
Music information retrieval
Blind source separation
Independent component analysis
Non-negative matrices
Auditory scene analysis
Signal processing--Digital techniques--Mathematics
Language:
English
DOI
https://doi.org/10.26300/pcpz-6m06

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Description

Abstract:
In this thesis, we give a review of modern blind, semi-blind, and informed source separation techniques. Specifically, the details of independent component analysis are derived, and several non-negative matrix factorization algorithms and adaptations are introduced. We focus on source separation applied to monaural musical signals in an attempt to develop a real-time musical decomposition system with applications in audio visualization, vocal recognition, karaoke generation, and more. Harmonic- percussive source separation algorithms are investigated, and a new filtering technique is proposed by defining a new transform space, the cepstromarg domain, which allows for instantaneous harmonic-percussive separation.
Notes:
Senior thesis (ScB)--Brown University, 2019
Concentration: Applied Mathematics

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Citation

Charous, Aaron, "Musical Source Separation: A Review of Techniques and the Proposal of Cepstromarg Filtering" (2019). Applied Mathematics Theses and Dissertations. Brown Digital Repository. Brown University Library. https://doi.org/10.26300/pcpz-6m06

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