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Volumn , Issue , 2011, Pages 783-788

Mining the correlation between lyrical and audio features and the emergence of mood

Author keywords

[No Author keywords available]

Indexed keywords

AUDIO FEATURES; CANONICAL CORRELATION ANALYSIS; GENRE IDENTIFICATION; GROUND TRUTH; MULTI-MODAL; RECOGNITION METHODS;

EID: 84872703021     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (31)

References (17)
  • 3
    • 84873578706 scopus 로고    scopus 로고
    • Mirex- 2010 single-label and multi-label classification tasks: Ircamclassification09 submission
    • J.J. Burred, M. Ramona, F. Cornu, and G. Peeters. Mirex- 2010 single-label and multi-label classification tasks: ircamclassification09 submission. MIREX 2010, 2010.
    • (2010) MIREX 2010
    • Burred, J.J.1    Ramona, M.2    Cornu, F.3    Peeters, G.4
  • 4
    • 84873572630 scopus 로고    scopus 로고
    • The Echo Nest Corp., too. May 2011
    • The Echo Nest Corp. The million song dataset gets lyrics, too. http://blog.echonest.com/post/4578901170/themillion-song-dataset-gets-lyrics- too May 2011.
    • The Million Song Dataset Gets Lyrics
  • 5
    • 58549098309 scopus 로고    scopus 로고
    • Language feature mining for music emotion classification via supervised learning from lyrics
    • H. He, J. Jin, Y. Xiong, B. Chen, W. Sun, and L. Zhao. Language feature mining for music emotion classification via supervised learning from lyrics. Advances in Computation and Intelligence, pages 426-435, 2008.
    • (2008) Advances in Computation and Intelligence , pp. 426-435
    • He, H.1    Jin, J.2    Xiong, Y.3    Chen, B.4    Sun, W.5    Zhao, L.6
  • 6
    • 0000107975 scopus 로고
    • Relations between two sets of variables
    • H. Hotelling. Relations between two sets of variables. Biometrika, 28:321-377, 1936.
    • (1936) Biometrika , vol.28 , pp. 321-377
    • Hotelling, H.1
  • 8
    • 84555199091 scopus 로고    scopus 로고
    • When lyrics outperform audio for music mood classification: A feature analysis
    • X. Hu and J.S. Downie. When lyrics outperform audio for music mood classification: a feature analysis. In ISMIR, pages 1-6, 2010.
    • (2010) ISMIR , pp. 1-6
    • Hu, X.1    Downie, J.S.2
  • 10
    • 84873686728 scopus 로고    scopus 로고
    • Lyric-based song emotion detection with affective lexicon and fuzzy clustering method
    • Y. Hu, X. Chen, and D. Yang. Lyric-based song emotion detection with affective lexicon and fuzzy clustering method. In Proceedings of ISMIR, 2009.
    • (2009) Proceedings of ISMIR
    • Hu, Y.1    Chen, X.2    Yang, D.3
  • 12
    • 84873607789 scopus 로고    scopus 로고
    • Svm-based audio classification, tagging, and similarity submissions
    • M.I. Mandel. Svm-based audio classification, tagging, and similarity submissions. MIREX 2010, 2010.
    • (2010) MIREX 2010
    • Mandel, M.I.1
  • 15
    • 84862293842 scopus 로고    scopus 로고
    • Using block-level features for genre classification, tag classification and music similarity estimation
    • K. Seyerlehner, M. Schedl, T. Pohle, and P. Knees. Using block-level features for genre classification, tag classification and music similarity estimation. MIREX 2010, 2010.
    • (2010) MIREX 2010
    • Seyerlehner, K.1    Schedl, M.2    Pohle, T.3    Knees, P.4


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.