Skip to main content
Book cover

Encyclopedia of Database Systems pp 2244–2249Cite as

Query by Humming

  • Reference work entry

  • 172 Accesses

Synonyms

Music retrieval; Time series database querying

Definition

With the appearance of large scale audio and video databases in various application areas, novel information retrieval methods adapted to the specific characteristics of these data types are required. A natural way of searching in a musical audio database is by humming the tune of a song as a query, which is so-called “query by humming”. In this entry, state-of-the-art techniques for effective and efficient querying by humming are described.

Historical Background

In 1995, Asif Ghias et al. [1] proposed the basic architecture for a system supporting query by humming. Three main components are introduced in the system: a pitch-tracking module, a melody database, and a query engine. Queries are hummed into a microphone, digitized, and fed into a pitch-tracking module. Then, a symbol sequence representation upon the relative pitch transitions of the hummed melody is sent to the query engine, which produces a ranked list of...

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

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-0-387-39940-9_292
  • Chapter length: 6 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   2,500.00
Price excludes VAT (USA)
  • ISBN: 978-0-387-39940-9
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Learn about institutional subscriptions
Query by Humming. Figure 1
 
Query by Humming. Figure 2

Recommended Reading

  1. Ghias A., Logan J., Chamberlin D., and Smith B.C. Query by humming: musical information retrieval in an audio database. In Proc. 3rd ACM Int. Conf. on Multimedia, 1995, pp. 231–236.

    Google Scholar 

  2. Keogh E.J. Exact indexing of dynamic time warping. In Proc. 28th Int. Conf. on Very Large Data Bases, 2002, pp. 406–417.

    Google Scholar 

  3. Zhou M. and Hon Wong M. Boundary-based lower-bound functions for dynamic time warping and their indexing. In Proc. 23rd Int. Conf. on Data Engineering, 2007, pp. 1307–1311.

    Google Scholar 

  4. Zhu Y. and Shasha D. Warping indexes with envelope transforms for query by humming. In Proc. ACM SIGMOD Int. Conf. on Management of Data, 2003, pp. 181–192.

    Google Scholar 

  5. Wai-Chee Fu A., Keogh E.J., Yung Hang Lau L., and Chotirat (Ann) Ratanamahatana. Scaling and time warping in time series querying. In Proc. 31st Int. Conf. on Very Large Data Bases, 2005, pp. 649–660.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Chinese University of Hong Kong, Hong Kong, China

    Yingyi Bu & Ada Wai-Chee Fu

  2. Hong Kong University of Science and Technology, Hong Kong, China

    Raymond Chi-Wing Wong

Authors
  1. Yingyi Bu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Raymond Chi-Wing Wong
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ada Wai-Chee Fu
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Professor, College of Computing, Georgia Institute of Technology, 266 Ferst Drive, 30332-0765, Atlanta, GA, USA

    LING LIU

  2. Professor and Director, University Research Chair, Database Research Group David R. Cheriton School of Computer Science, University of Waterloo, 200 University Avenue West, N2L 3G1, Waterloo, ON, Canada

    M. TAMER ÖZSU

Rights and permissions

Reprints and Permissions

Copyright information

© 2009 Springer Science+Business Media, LLC

About this entry

Cite this entry

Bu, Y., Chi-Wing Wong, R., Fu, AC. (2009). Query by Humming. In: LIU, L., ÖZSU, M.T. (eds) Encyclopedia of Database Systems. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-39940-9_292

Download citation