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Audio Source Separation

Overview of attention for book
Cover of 'Audio Source Separation'

Table of Contents

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    Book Overview
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    Chapter 1 Single-Channel Audio Source Separation with NMF: Divergences, Constraints and Algorithms
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    Chapter 2 Separation of Known Sources Using Non-negative Spectrogram Factorisation
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    Chapter 3 Dynamic Non-negative Models for Audio Source Separation
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    Chapter 4 An Introduction to Multichannel NMF for Audio Source Separation
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    Chapter 5 General Formulation of Multichannel Extensions of NMF Variants
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    Chapter 6 Determined Blind Source Separation with Independent Low-Rank Matrix Analysis
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    Chapter 7 Deep Neural Network Based Multichannel Audio Source Separation
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    Chapter 8 Efficient Source Separation Using Bitwise Neural Networks
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    Chapter 9 DNN Based Mask Estimation for Supervised Speech Separation
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    Chapter 10 Informed Spatial Filtering Based on Constrained Independent Component Analysis
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    Chapter 11 Recent Advances in Multichannel Source Separation and Denoising Based on Source Sparseness
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    Chapter 12 Multimicrophone MMSE-Based Speech Source Separation
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    Chapter 13 Musical-Noise-Free Blind Speech Extraction Based on Higher-Order Statistics Analysis
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    Chapter 14 Audio-Visual Source Separation with Alternating Diffusion Maps
Attention for Chapter 2: Separation of Known Sources Using Non-negative Spectrogram Factorisation
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Citations

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Chapter title
Separation of Known Sources Using Non-negative Spectrogram Factorisation
Chapter number 2
Book title
Audio Source Separation
Published by
Springer, Cham, January 2018
DOI 10.1007/978-3-319-73031-8_2
Book ISBNs
978-3-31-973030-1, 978-3-31-973031-8
Authors

Tuomas Virtanen, Tom Barker

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 1 Mendeley reader of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 1 100%
Readers by discipline Count As %
Engineering 1 100%

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