NDLI: Solely Tag-Based Music Genre Classification

Content Provider	IEEE Xplore Digital Library
Author	Chao Zhen Jieping Xu
Copyright Year	2010
Abstract	As a fundamental and critical component of music information retrieval (MIR) systems, automatically classifying music by genre is a challenging problem. The approaches depending on low-level audio features may not be able to obtain satisfactory results. In recent years, the social tags have emerged as an important way to provide information about resources on the Web. In this paper we are interested in another aspect, namely how perform automatic music genre classification solely depending on the available tag data. Two classification methods based on the social tags (including music-tag and artist-tag) which crawled from Last. fm are developed in our work. The first one, we use the generative probabilistic model Latent Dirichlet Allocation (LDA) to analyze the music-tag. Then, we can compute the probability of every tag belonging to each music genre. The starting point of the second method is that music’s artist is often associated with music genres more closely. Therefore, we can calculate the similarity between the artist-tags to infer which genre the music belongs to. At last, our experimental results demonstrate the benefit of using tags for accurate music genre classification.
Starting Page	20
Ending Page	24
File Size	359788
Page Count	5
File Format	PDF
ISBN	9781424484386
DOI	10.1109/WISM.2010.152
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-10-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Decision support systems Music genre classification Music tag Artist tag LDA Delta modulation Helium
Content Type	Text
Resource Type	Article

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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	Mr. Siddhartha Mukherjee siddhartha@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	ndl-support@iitkgp.ac.in
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