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An Adaptation Framework for QBH-Based Music Retrieval

  • Seungmin Rho
  • Byeong-jun Han
  • Eenjun Hwang
  • Minkoo Kim
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4692)

Abstract

In this paper, we present a new music query transcription and refinement scheme for efficient music retrieval. For the accurate music query transcription into symbolic representation, we propose a method called WAE for note onset detection, and DTC for ADF onset detection. Also, in order to improve the retrieval performance, we propose a new relevance feedback scheme using genetic algorithm. We have built a prototype system based on this scheme and performed various experiments. Experimental results show that our proposed scheme achieves a good performance.

Keywords

Genetic Algorithm Music Retrieval Relevance Feedback 

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References

  1. 1.
    Rho, S., Hwang, E.: FMF: Query adaptive melody retrieval system. Journal of Systems and Software (JSS) 79(1), 43–56 (2006)CrossRefGoogle Scholar
  2. 2.
    Pickens, J.: A Comparison of Language Modeling and Probabilistic Text Information Retrieval Approaches to Monophonic Music Retrieval. In: Proceedings of the International Symposium on Information Retrieval (ISMIR), Plymouth, Massachusetts, (October 2000)Google Scholar
  3. 3.
    Lemstrom, K., Wiggins, G.A., Meredith, D.: A three layer approach for music retrieval in large databases. In: 2nd International Symposium on Music Information Retrieval, Bloomington, IN, USA, pp. 13–14 (2001)Google Scholar
  4. 4.
    Hoashi, Matsumoto, Inoue.: Personalization of User Profiles for Content-based Music Retrieval Based on Relevance Feedback. ACM Multimedia, 110–119 (2003)Google Scholar
  5. 5.
  6. 6.
    Lopez-Pujalte, C., Guerrero-Bote, V., Moya-Anegon, F.: Order-based Fitness functions for genetic algorithms applied to relevance feedback. Journal of the American Society for Information Science 54(2), 152–160 (2003)CrossRefGoogle Scholar
  7. 7.
    Gerhard, D.: Pitch Extraction and Fundamental Frequency: History and Current Techniques. In: Technical Report TR-CS 2003-06 (November 2003)Google Scholar
  8. 8.
    Park, S., Kim, S., Byeon, K., Hwang, E.: Automatic Voice Query Transformation for Query-by-Humming Systems. In: Proc. of the IMSA 2005, pp. 197–202 (August 2005)Google Scholar
  9. 9.
    Chai, W.: Melody Retrieval On the Web. In: Requirements of the degree of Master of Science in Media Arts and Sciences at the Massachusetts Institute of Technology (2001)Google Scholar
  10. 10.
    Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. Addison Wesley, London, UK (1999)Google Scholar
  11. 11.
    Han, B., Rho, S., Hwang, E.: An Efficient Voice Transcription Scheme for Music Retrieval. In: Proc. of the IEEE MUE 2007, Seoul, Korea, pp. 366–371 (2007)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2007

Authors and Affiliations

  • Seungmin Rho
    • 1
  • Byeong-jun Han
    • 2
  • Eenjun Hwang
    • 2
  • Minkoo Kim
    • 1
  1. 1.Graudate School of Information and Communication, Ajou University, SuwonKorea
  2. 2.Department of Electronics and Computer Engineering, Korea University, SeoulKorea

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