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CD-ARES 2012: Multidisciplinary Research and Practice for Information Systems pp 259–271Cite as

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Indexing and Search for Fast Music Identification

Indexing and Search for Fast Music Identification

  • Guang-Ho Cha21 
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Part of the Lecture Notes in Computer Science book series (LNISA,volume 7465)

Abstract

In this paper, we present a new technique for indexing and search in a database that stores songs. A song is represented by a high dimensional binary vector using the audio fingerprinting technique. Audio fingerprinting extracts from a song a fingerprint which is a content-based compact signature that summarizes an audio recording. A song can be recognized by matching an extracted fingerprint to a database of known audio fingerprints. In this paper, we are given a high dimensional binary fingerprint database of songs and focus our attention on the problem of effective and efficient database search. However, the nature of high dimensionality and binary space makes many modern search algorithms inapplicable. The high dimensionality of fingerprints suffers from the curse of dimensionality, i.e., as the dimension increases, the search performance decreases exponentially. In order to tackle this problem, we propose a new search algorithm based on inverted indexing, the multiple sub-fingerprint match principle, the offset match principle, and the early termination strategy. We evaluate our technique using a database of 2,000 songs containing approximately 4,000,000 sub-fingerprints and the experimental result shows encouraging performance.

This study was financially supported by Seoul National University of Science and Technology.

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References

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Author information

Authors and Affiliations

  1. Seoul National University of Science and Technology, Seoul, 139-743, Republic of Korea

    Guang-Ho Cha

Authors
  1. Guang-Ho Cha
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Editor information

Editors and Affiliations

  1. Department of IT, Engineering and Environment, University of South Australia, Mawson Lakes Campus, 5001, Adelaide, SA, Australia

    Gerald Quirchmayr

  2. Department of Information Technologies, University of Economics, W. Churchill Sq. 4, 130 67, Prague 3, Czech Republic

    Josef Basl

  3. School of Information Science, Korean Bible University, 16 Danghyun 2-gil, Nowon-gu, 139-791, Seoul, Korea

    Ilsun You

  4. Information Technology and Decision Sciences, Old Dominion University, 2076 Constant Hall, 23529, Norfolk, VA, USA

    Lida Xu

  5. Institute of Software Technology and Interactive Systems, Vienna University of Technology and SBA Research, Favoritenstrsse 9-11, 1040, Vienna, Austria

    Edgar Weippl

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© 2012 IFIP International Federation for Information Processing

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Cite this paper

Cha, GH. (2012). Indexing and Search for Fast Music Identification. In: Quirchmayr, G., Basl, J., You, I., Xu, L., Weippl, E. (eds) Multidisciplinary Research and Practice for Information Systems. CD-ARES 2012. Lecture Notes in Computer Science, vol 7465. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32498-7_20

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  • DOI: https://doi.org/10.1007/978-3-642-32498-7_20

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