• DocumentCode
    2694708
  • Title

    Audio tonality mode classification without tonic annotations

  • Author

    Duan, Zhiyao ; Lu, Lie ; Zhang, Changshui

  • fYear
    2008
  • fDate
    June 23 2008-April 26 2008
  • Firstpage
    1361
  • Lastpage
    1364
  • Abstract
    Traditional tonality mode (major or minor) classification or audio key finding algorithms often rely on tonic annotations (key names) of the training songs. However, unlike classical music whose keys are usually explicitly labeled in their titles, the keys of numerous popular music are hard to obtain. In contrast, it is much easier to only label the mode for each song. With only modes labeled, traditional approaches to key or mode classification cannot be directly applied, due to the lack of the reference point to transpose and align the chroma features with different keys. In this paper, we present an alignment approach to transpose chroma features within each mode to a reference (but unknown) tonic. Then several methods, including Single Profile Correlation, Multiple Profile Correlation and Support Vector Machine, are exploited to address mode learning and classification. Experimental results show the feasibility of the proposed approach.
  • Keywords
    audio coding; music; audio tonality mode classification; mode learning; multiple profile correlation; single profile correlation; support vector machine; Adaptive arrays; Asia; Automation; Hidden Markov models; Information science; Intelligent systems; Laboratories; Music information retrieval; Spirals; Training data; Audio key finding; Music information retrieval; Tonality classification;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Multimedia and Expo, 2008 IEEE International Conference on
  • Conference_Location
    Hannover
  • Print_ISBN
    978-1-4244-2570-9
  • Electronic_ISBN
    978-1-4244-2571-6
  • Type

    conf

  • DOI
    10.1109/ICME.2008.4607696
  • Filename
    4607696