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Volumn , Issue , 2008, Pages 127-131

Automatic genre and artist classification by analyzing improvised solo parts from musical recordings

Author keywords

[No Author keywords available]

Indexed keywords

AUDIO DATA; CONTENT-BASED; DISCRIMINATIVE POWER; HIGH-LEVEL FEATURES; TEST SETS;

EID: 84876934064     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (6)

References (15)
  • 3
    • 0036748814 scopus 로고    scopus 로고
    • AI and music: From composition to expressive performances
    • R. Lopez de Mantaras and J. L. Arcos. AI and music: From composition to expressive performances. AI Magazine, 23:43-57, 2002.
    • (2002) AI Magazine , vol.23 , pp. 43-57
    • De Mantaras Lopez, R.1    Arcos, J.L.2
  • 10
    • 0035440862 scopus 로고    scopus 로고
    • Discovering nontrivial repeating patterns in music data
    • September
    • J.-L. Hsu, C.-C. Liu, and A. L. P. Chen. Discovering nontrivial repeating patterns in music data. In IEEE Transactions on Multimedia, volume 3, pages 311-324, September 2001.
    • (2001) IEEE Transactions on Multimedia , vol.3 , pp. 311-324
    • Hsu, J.-L.1    Liu, C.-C.2    Chen, A.L.P.3
  • 15
    • 33646192105 scopus 로고    scopus 로고
    • Computational models of expressive music performance: The state of the art
    • G. Widmer and W. Goebl. Computational models of expressive music performance: The state of the art. In Journal of New Music Research, volume 33, pages 203-216, 2004.
    • (2004) Journal of New Music Research , vol.33 , pp. 203-216
    • Widmer, G.1    Goebl, W.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.