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Kara1k: A Karaoke Dataset for Cover Song Identification and Singing Voice Analysis

Identifikátory výsledku

  • Kód výsledku v IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F18%3A10240412" target="_blank" >RIV/61989100:27740/18:10240412 - isvavai.cz</a>

  • Výsledek na webu

    <a href="https://ieeexplore.ieee.org/document/8241597" target="_blank" >https://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>

Alternativní jazyky

  • Jazyk výsledku

    angličtina

  • Název v původním jazyce

    Kara1k: A Karaoke Dataset for Cover Song Identification and Singing Voice Analysis

  • Popis výsledku v původním jazyce

    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 application1, 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&apos;s gender, backing vocals, duets and lyrics&apos; 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 website2.

  • Název v anglickém jazyce

    Kara1k: A Karaoke Dataset for Cover Song Identification and Singing Voice Analysis

  • Popis výsledku anglicky

    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 application1, 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&apos;s gender, backing vocals, duets and lyrics&apos; 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 website2.

Klasifikace

  • Druh

    D - Stať ve sborníku

  • CEP obor

  • OECD FORD obor

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Návaznosti výsledku

  • Projekt

    Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

  • Návaznosti

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Ostatní

  • Rok uplatnění

    2018

  • Kód důvěrnosti údajů

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Údaje specifické pro druh výsledku

  • Název statě ve sborníku

    Proceedings - 2017 IEEE International Symposium on Multimedia, ISM 2017

  • ISBN

    978-1-5386-2936-9

  • ISSN

  • e-ISSN

    neuvedeno

  • Počet stran výsledku

    8

  • Strana od-do

    177-184

  • Název nakladatele

    IEEE

  • Místo vydání

    Piscataway

  • Místo konání akce

    Tchaj-čung

  • Datum konání akce

    11. 12. 2017

  • Typ akce podle státní příslušnosti

    WRD - Celosvětová akce

  • Kód UT WoS článku