• DocumentCode
    166241
  • Title

    Using the Echo Nest´s automatically extracted music features for a musicological purpose

  • Author

    Andersen, Jesper Steen

  • Author_Institution
    R. Sch. of Libr. & Inf. Sci., Univ. of Copenhagen, Copenhagen, Denmark
  • fYear
    2014
  • fDate
    26-28 May 2014
  • Firstpage
    1
  • Lastpage
    6
  • Abstract
    This paper sums up the preliminary observations and challenges encountered during my first engaging with the music intelligence company Echo Nest´s automatically derived data of more than 35 million songs. The overall purpose is to investigate whether musicologists can draw benefit from Echo Nest´s API, and to explore what practical and analytical consideration one should take into account when engaging with the numbers derived from the Echo Nest API. This paper suggests that the Echo Nest API hold a large potential of doing new types of analyses and visualizing the results. But it concurrently argues that a careful and critical approach is requisite, when interpreting the results.
  • Keywords
    application program interfaces; feature extraction; information retrieval; music; Echo Nest API; Echo Nest music intelligence company; automatic music feature extraction; musicologist; Algorithm design and analysis; Correlation; Educational institutions; Manuals; Music; Music information retrieval; Music information retrieval; digital humanities; information science; musicology;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Cognitive Information Processing (CIP), 2014 4th International Workshop on
  • Conference_Location
    Copenhagen
  • Type

    conf

  • DOI
    10.1109/CIP.2014.6844510
  • Filename
    6844510