NDLI: Instrumentation-based music similarity using sparse representations

Content Provider	IEEE Xplore Digital Library
Author	Fujihara, H. Klapuri, A. Plumbley, M.D.
Copyright Year	2012
Description	Author affiliation: Queen Mary University of London, Centre for Digital Music, UK (Fujihara, H.; Klapuri, A.; Plumbley, M.D.)
Abstract	This paper describes a novelmusic similarity calculation method that is based on the instrumentation of music pieces. The approach taken here is based on the idea that sparse representations of musical audio signals are a rich source of information regarding the elements that constitute the observed spectra. We propose a method to extract feature vectors based on sparse representations and use these to calculate a similarity measure between songs. To train a dictionary for sparse representations from a large amount of training data, a novel dictionary-initialization method based on agglomerative clustering is proposed. An objective evaluation shows that the new features improve the performance of similarity calculation compared to the standard mel-frequency cepstral coefficients features.
Starting Page	433
Ending Page	436
File Size	327411
Page Count	4
File Format	PDF
ISBN	9781467300452
ISSN	15206149
e-ISBN	9781467300469
e-ISBN	9781467300445
DOI	10.1109/ICASSP.2012.6287909
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-03-25
Publisher Place	Japan
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Dictionaries Instruments Vectors Feature extraction Sparse matrices Encoding Indexes Online dictionary learning Music similarity Instrumentation Sparse representation
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Music genre classification using On-line Dictionary Learning

Signal classification based on block-sparse tensor representation

K-WEB: Nonnegative dictionary learning for sparse image representations

Online adaptive dictionary learning and weighted sparse coding for abnormality detection

Are Sparse Representation and Dictionary Learning Good for Handwritten Character Recognition?

Sparsity-based representation for categorical data

Outlier-aware dictionary learning for sparse representation

Object co-detection via low-rank and sparse representation dictionary learning

A novel multi-feature fusion and sparse coding-based framework for image retrieval

Instrumentation-based music similarity using sparse representations

Similar Documents

Music genre classification using On-line Dictionary Learning

Signal classification based on block-sparse tensor representation

K-WEB: Nonnegative dictionary learning for sparse image representations

Online adaptive dictionary learning and weighted sparse coding for abnormality detection

Are Sparse Representation and Dictionary Learning Good for Handwritten Character Recognition?

Sparsity-based representation for categorical data

Outlier-aware dictionary learning for sparse representation

Object co-detection via low-rank and sparse representation dictionary learning

A novel multi-feature fusion and sparse coding-based framework for image retrieval

Instrumentation-based music similarity using sparse representations