NDLI: Homotopy optimisation based NMF for audio source separation

Content Provider	IET Digital Library
Author	Koundinya, Sriharsha Karmakar, Abhijit
Abstract	In this study, the authors propose a novel framework for audio source separation based on a cascaded non-negative matrix factorisation (NMF) using homotopy optimisation with perturbation and ensemble (HOPE) and denoising autoencoder. NMF using traditional optimisation has a problem of finding a global solution, and hence could not achieve complete separation of the sources from the mixture. This problem has been addressed using homotopy optimisation in this study. Subsequently, using denoising autoencoder the residual sounds that are usually observed in the separated sources are removed. The enhanced audio signals are filtered using Wiener techniques to obtain the separated signals. The homotopy-based NMF is applied for separating singing voice and drums from song samples using a single-channel mixture. The separated signals are compared with other NMF algorithms by using Blind Source Separation (BSS) Eval objective quality measures. The NMF with HOPE and denoising autoencoder is shown to provide an improvement of up to 6 dB in comparison with other NMF algorithms.
Starting Page	1099
Ending Page	1106
Page Count	8
ISSN	17519675
Volume Number	12
e-ISSN	17519683
Issue Number	Issue 9, Dec (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-spr/12/9
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-spr.2018.5093
Journal	IET Signal Processing
Publisher Date	2018-07-17
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Algebra Audio Signal Processing Audio Source Separation Blind Source Separation Complete Separation Denoising Autoencoder Digital Signal Processing Drums Enhanced Audio Signal Homotopy Optimisation-based NMF Homotopy-based NMF Matrix Decomposition NMF Algorithm Noise Figure 6.0 DB Nonnegative Matrix Factorisation Separated Signal Separated Source Separating Singing Voice Signal Processing And Detection Source Separation Speech And Audio Signal Processing Statistics Traditional Optimisation
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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