Skip to main content

A Music Retrieval System Based on Query-by-Singing for Karaoke Jukebox

  • Conference paper
Information Retrieval Technology (AIRS 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4182))

Included in the following conference series:

  • 957 Accesses

Abstract

This paper investigates the problem of retrieving Karaoke music by singing. The Karaoke music encompasses two audio channels in each track: one is a mix of vocal and background accompaniment, and the other is composed of accompaniment only. The accompaniments in the two channels often resemble each other, but are not identical. This characteristic is exploited to infer the vocal’s background music from the accompaniment-only channel, so that the main melody underlying the vocal signals can be extracted more effectively. To enable an efficient and accurate search for a large music database, we propose a phrase onset detection method based on Bayesian Information Criterion (BIC) for predicting the most likely beginning of a sung query, and adopt a multiple-level multiple-pass Dynamic Time Warping (DTW) for melody similarity comparison. The experiments conducted on a Karaoke database consisting of 1,071 popular songs show the promising results of query-by-singing retrieval for Karaoke music.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Ghias, A., Logan, H., Chamberlin, D., Smith, B.C.: Query by Humming: Musical Information Retrieval in an Audio Database. In: Proc. ACM International Conference on Multimedia (1995)

    Google Scholar 

  2. Kosugi, N., Nishihara, Y., Sakata, T., Yamamuro, M., Kushima, K.: Music Retrieval by Humming. In: Proc. IEEE Pacific Rim Conference on Communications, Computers and Signal Processing (1999)

    Google Scholar 

  3. Kosugi, N., Nishihara, Y., Sakata, T., Yamamuro, M., Kushima, K.: A Practical Query- By-Humming System for a Large Music Database. In: Proc. ACM International Conference on Multimedia (2000)

    Google Scholar 

  4. Nishimura, T., Hashiguchi, H., Takita, J., Zhang, J.X., Goto, M., Oka, R.: Music Signal Spotting Retrieval by a Humming Query Using Start Frame Feature Dependent Continuous Dynamic Programming. In: Proc. International Symposium on Music Information Retrieval (2001)

    Google Scholar 

  5. Roger, J.J.S., Lee, H.R.: Hierarchical Filtering Method for Content-based Music Retrieval via Acoustic Input. In: Proc. ACM International Conference on Multimedia (2001)

    Google Scholar 

  6. Song, J., Bae, S.Y., Yoon, K.: Mid-Level Music Melody Representation of Polyphonic Audio for Query-by-Humming System. In: Proc. International Conference on Music Information Retrieval (2002)

    Google Scholar 

  7. Yu, H.M., Tsai, W.H., Wang, H.M.: A Query-by-singing Technique for Retrieving Polyphonic Objects of Popular Music. In: Proc. Asian Information Retrieval Symposium (2005)

    Google Scholar 

  8. Doraisamy, S., Ruger, S.M.: An Approach Towards a Polyphonic Music Retrieval System. In: Proc. International Symposium on Music Information Retrieval (2001)

    Google Scholar 

  9. Goto, M.: A Predominant-F0 Estimation Method for CD Recordings: MAP Estimation Using EM Algorithm for Adaptive Tone Models. In: Proc. IEEE International Conference on Acoustics, Speech, and Signal Processing (2001)

    Google Scholar 

  10. Doraisamy, S., Rüger, S.: Robust Polyphonic Music Retrieval with N-grams. Journal of Intelligent Information Systems 21(1), 53–70 (2003)

    Article  Google Scholar 

  11. Liu, C.C., Hsu, A.J.L., Chen, A.L.P.: An Approximate String Matching Algorithm for Content-Based Music Data Retrieval. In: Proc. IEEE International Conference on Multimedia Computing and Systems (1999)

    Google Scholar 

  12. Mo, J.S., Han, C.H., Kim, Y.S.: A Melody-Based Similarity Computation Algorithm for Musical Information. In: Proc. Workshop on Knowledge and Data Engineering Exchange (1999)

    Google Scholar 

  13. Shifrin, J., Burmingham, W.: Effectiveness of HMM-based Retrieval on Large Databases. In: Proc. International Conference on Music Information Retrieval (2003)

    Google Scholar 

  14. Keogh, E., Pazzani, M.: Scaling up Dynamic Time Warping for Datamining Applications. In: Proc. ACM SIGKDD (2000)

    Google Scholar 

  15. Salvador, S., Chan, P.: FastDTW: Toward Accurate Dynamic Time Warping in Linear Time and Space. In: Proc. KDD Workshop on Mining Temporal and Sequential Data (2004)

    Google Scholar 

  16. Schwarz, G.: Estimation the Dimension of a Model. The Annals of Statistics 6, 461–364 (1978)

    Google Scholar 

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

Yu, HM., Tsai, WH., Wang, HM. (2006). A Music Retrieval System Based on Query-by-Singing for Karaoke Jukebox. In: Ng, H.T., Leong, MK., Kan, MY., Ji, D. (eds) Information Retrieval Technology. AIRS 2006. Lecture Notes in Computer Science, vol 4182. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11880592_34

Download citation

  • DOI: https://doi.org/10.1007/11880592_34

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-45780-0

  • Online ISBN: 978-3-540-46237-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics