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An Adaptation Framework for QBH-Based Music Retrieval

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Part of the book series: Lecture Notes in Computer Science ((LNAI,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.

This research was partially supported by the MIC, Korea, under the ITRC support program supervised by the IITA. (IITA-2006-(C1090-0603-0002)) and by the Ubiquitous Computing and Network (UCN) Project, the Ministry of Information and Communication (MIC) 21st Century Frontier R&D Program in Korea.

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References

  1. Rho, S., Hwang, E.: FMF: Query adaptive melody retrieval system. Journal of Systems and Software (JSS) 79(1), 43–56 (2006)

    Article  Google Scholar 

  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. 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. Hoashi, Matsumoto, Inoue.: Personalization of User Profiles for Content-based Music Retrieval Based on Relevance Feedback. ACM Multimedia, 110–119 (2003)

    Google Scholar 

  5. Foote, The TreeQ Package, ftp://svr-ftp.eng.cam.ac.uk/pub/comp.speech/tools/treeq1.3.tar.gz

  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)

    Article  Google Scholar 

  7. Gerhard, D.: Pitch Extraction and Fundamental Frequency: History and Current Techniques. In: Technical Report TR-CS 2003-06 (November 2003)

    Google Scholar 

  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. 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. Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. Addison Wesley, London, UK (1999)

    Google Scholar 

  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 

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Bruno Apolloni Robert J. Howlett Lakhmi Jain

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© 2007 Springer-Verlag Berlin Heidelberg

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Rho, S., Han, Bj., Hwang, E., Kim, M. (2007). An Adaptation Framework for QBH-Based Music Retrieval. In: Apolloni, B., Howlett, R.J., Jain, L. (eds) Knowledge-Based Intelligent Information and Engineering Systems. KES 2007. Lecture Notes in Computer Science(), vol 4692. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74819-9_74

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  • DOI: https://doi.org/10.1007/978-3-540-74819-9_74

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74817-5

  • Online ISBN: 978-3-540-74819-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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