• DocumentCode
    2802124
  • Title

    How similar do songs sound? Towards modeling human perception of musical similarity

  • Author

    Herre, Jürgen ; Allamanche, Eric ; Ertel, Chris

  • Author_Institution
    Fraunhofer Inst. for Integrated Circuits FhG-IIS, Erlangen, Germany
  • fYear
    2003
  • fDate
    19-22 Oct. 2003
  • Firstpage
    83
  • Lastpage
    86
  • Abstract
    Human listeners have a well-developed feeling for identifying "whether two songs sound similar" or whether they do not. Even though this type of judgment usually also involves a considerable amount of the listener\´s background knowledge, it has been demonstrated that an algorithmic model of this type of similarity can be achieved by merely evaluating the signal\´s low-level acoustic features. The paper describes a system for assessing subjectively sound similarity between pairs of musical items by using a number of such signal features. The system\´s performance is assessed by means of a subjective listening test that is based on a modification of a test methodology originally standardized for subjective sound quality evaluation. A number of interesting applications for such a technology are described.
  • Keywords
    acoustic signal processing; audio signal processing; feature extraction; hearing; music; feature extraction; human perception; low-level acoustic features; musical similarity; signal features; song similarity; subjective listening test; subjective sound similarity assessment; Acoustic measurements; Acoustic testing; Algorithm design and analysis; Cepstral analysis; Emulation; Feature extraction; Humans; Integrated circuit modeling; Signal processing algorithms; System testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Applications of Signal Processing to Audio and Acoustics, 2003 IEEE Workshop on.
  • Print_ISBN
    0-7803-7850-4
  • Type

    conf

  • DOI
    10.1109/ASPAA.2003.1285825
  • Filename
    1285825