Skip to main content

Beyond Error Tolerance: Finding Thematic Similarities in Music Digital Libraries

  • Conference paper

Part of the Lecture Notes in Computer Science book series (LNISA,volume 4172)

Abstract

Current Music Information Retrieval (MIR) systems focus on melody based retrieval with some tolerance for user errors in the melody specification. The system described here presents a novel method for theme retrieval: A theme is described as a list of musical events, containing melody and harmony features, which must be presented in a given order and within a given time frame. The system retrieves musical phrases that fit the description. A system of this type could serve musicians and listeners who wish to discover thematically similar phrases in music digital libraries. The prototype and underlying model have been tested on midi sequences of music by W.A. Mozart and have shown good performance results.

Keywords

  • User Error
  • Music Information Retrieval
  • Musical Event
  • Good Performance Result
  • Pitch Class

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This is a preview of subscription content, access via your institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/11863878_44
  • Chapter length: 4 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   99.00
Price excludes VAT (USA)
  • ISBN: 978-3-540-44638-5
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   129.99
Price excludes VAT (USA)

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Barlow, H., Morgenstern, S.: A Dictionary of Musical Themes (1948)

    Google Scholar 

  2. The Multimedia Library, http://www.multimedialibrary.com/barlow/

  3. Downie, J.S., Nelson, M.: Evaluation of a Simple and Effective Music Information Retrieval Method. In: 23rd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, Athens, Greece (2000)

    Google Scholar 

  4. Birmingham, W.P., Dannenberg, R.B., Wakefield, G.H., Bartsch, M., Bykowski, D., Mazzoni, D., Meek, C., Mellody, M., Rand, W.: Musart: Music Retrieval via Aural Queries. In: ISMIR 2001, Bloomington, Indiana (2001)

    Google Scholar 

  5. McNab, R.J., Smith, L.A., Witten, I.H., Henderson, C.L., Cunningham, S.J.: Towards the Digital Music Library: Tune Retrieval from Acoustic Input. Digital Libraries (1996)

    Google Scholar 

  6. Classical Music Archives, http://www.classicalarchives.com

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Berman, T., Downie, J.S., Berman, B. (2006). Beyond Error Tolerance: Finding Thematic Similarities in Music Digital Libraries. In: Gonzalo, J., Thanos, C., Verdejo, M.F., Carrasco, R.C. (eds) Research and Advanced Technology for Digital Libraries. ECDL 2006. Lecture Notes in Computer Science, vol 4172. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11863878_44

Download citation

  • DOI: https://doi.org/10.1007/11863878_44

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44636-1

  • Online ISBN: 978-3-540-44638-5

  • eBook Packages: Computer ScienceComputer Science (R0)