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Audio Content Analysis

  • Living reference work entry
  • First Online:
Encyclopedia of Database Systems

  • 59 Accesses

Synonyms

Audio information retrieval; Semantic inference in audio

Definition

An audio signal is a signal that contains information in the audible frequency range. Audio content analysis refers to a set of theories, algorithms and systems that aim at extracting descriptors or metadata related to audio content and allowing search, retrieval and other user actions performed on audio signals.

Historical Background

Multimedia content analysis has been one of the most booming research directions in the past years. With the objective of providing fast, natural, intuitive and personalized content-based access to vast multimedia data collections, and building on the synergy of many scientific disciplines, such as signal processing, pattern recognition, machine learning, information retrieval, information theory, natural language processing and psychology, the research initiative born around the end of the 1980s has succeeded in inspiring and mobilizing enormous number of researchers worldwide....

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Recommended Reading

  1. Cai R, Lu L, Hanjalic A. Unsupervised content discovery in composite audio. In: Proceedings of the IEEE International Conference on Multimedia and Expo; 2005. p. 628–37.

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  2. Cai R, Lu L, Hanjalic A, Zhang H-J, Cai L-H. A flexible framework for key audio effects detection and auditory context inference. IEEE Trans Audio Speech Lang Process. 2006;14(3):1026–39.

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  3. Casey M, et al. Content-based music information retrieval: current directions and future challenges. In: Proceedings of the IEEE, Special Issue on Advances in Multimedia Information Retrieval. 2008;96(4):668–96.

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  5. Hanjalic A. Content-based analysis of digital video. Norwell: Kluwer; 2004.

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  6. Huang X, Acero A, Hon HW. Spoken language processing: a guide to theory, algorithm, and system development. Upper Saddle River: Prentice; 2001.

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  7. Lu L, Cai R, Hanjalic A. Audio elements based auditory scene segmentation. Proc IEEE Int Conf Acoust Speech Signal Process. 2006;5:17–20.

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  8. Lu L, Zhang H-J, Jiang H. Content analysis for audio classification and segmentation. IEEE Trans Speech Audio Process. 2002;10(7):504–16.

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  9. Radhakrishnan R, Divakaran A, Xiong Z. A time series clustering based framework for multimedia mining and summarization using audio features. In: Proceedings of the 6th ACM SIGMM International Workshop on Multimedia Information Retrieval; 2004. p. 157–64.

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Author information

Authors and Affiliations

  1. Microsoft Research Asia, Beijing, China

    Lie Lu

  2. Delft University of Technology, Delft, The Netherlands

    Alan Hanjalic

Authors
  1. Lie Lu
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  2. Alan Hanjalic
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Corresponding author

Correspondence to Lie Lu .

Editor information

Editors and Affiliations

  1. Georgia Institute of Technology College of Computing, Atlanta, Georgia, USA

    Ling Liu

  2. University of Waterloo School of Computer Science, Waterloo, Ontario, Canada

    M. Tamer Özsu

Section Editor information

  1. Dept. of Computer Science, New Jersey Inst. of Technology, University Heights, 7102, Newark, NJ, USA

    Vincent Oria

  2. Digital Content and Media Sciences ReseaMultimedia Information Research Division, National Institute of Informatics, Tokyo, Japan

    Shin'ichi Satoh

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© 2016 Springer Science+Business Media LLC

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Lu, L., Hanjalic, A. (2016). Audio Content Analysis. In: Liu, L., Özsu, M. (eds) Encyclopedia of Database Systems. Springer, New York, NY. https://doi.org/10.1007/978-1-4899-7993-3_1528-2

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  • DOI: https://doi.org/10.1007/978-1-4899-7993-3_1528-2

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  • Publisher Name: Springer, New York, NY

  • Online ISBN: 978-1-4899-7993-3

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

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