Kara1k: a karaoke dataset for cover song identification and singing voice analysis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F17%3A10363153" target="_blank" >RIV/00216208:11320/17:10363153 - isvavai.cz</a>
Result on the web
<a href="http://ieeexplore.ieee.org/document/8241597/" target="_blank" >http://ieeexplore.ieee.org/document/8241597/</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ISM.2017.32" target="_blank" >10.1109/ISM.2017.32</a>
Alternative languages
Result language
angličtina
Original language name
Kara1k: a karaoke dataset for cover song identification and singing voice analysis
Original language description
We introduce Kara1k, a new musical dataset composed of 2,000 analyzed songs thanks to a partnership with a karaoke company. The dataset is divided into 1,000 cover songs provided by Recisio Karafun application, and the corresponding 1,000 songs by the original artists. Kara1k is mainly dedicated toward cover song identification and singing voice analysis. For both tasks, it offers novel approaches, as each cover song is a studio-recorded song with the same arrangement as the original recording, but with different singers and musicians. Essentia, harmony-analyser, Marsyas, Vamp plugins and YAAFE have been used to extract audio features for each track in Kara1k. We provide metadata such as the title, genre, original artist, year, International Standard Recording Code and the ground truths for the singer's gender, backing vocals, duets and lyrics' language. Additionally, we provide the instrumental track and the pure singing voice track for each cover song. We showcase two use-case experiments for Kara1k. In the cover song identification task using the Dynamic Time Warping method, we provide a comparison of traditional and new features: chroma and MFCC features, chords and keys, and chroma and chord distances. We obtain 84-89% identification accuracy for three of the features, which justifies our focus on karaoke songs. In the supporting experiment on singer gender classification, we evaluate the difference in the performance in two conditions - a pure singing voice and the singing voice mixed with the background music. The Kara1k dataset is freely available under the KaraMIR project website.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2017 IEEE International Symposium on Multimedia (ISM)
ISBN
978-1-5386-2937-6
ISSN
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e-ISSN
neuvedeno
Number of pages
8
Pages from-to
177-184
Publisher name
IEEE
Place of publication
Taichung, Taiwan
Event location
Taichung, Taiwan
Event date
Dec 11, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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