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Classification Methods for Speaker Recognition

  • Chapter
Speaker Classification I

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 4343))

Abstract

Automatic speaker recognition systems have a foundation built on ideas and techniques from the areas of speech science for speaker characterization, pattern recognition and engineering. In this chapter we provide an overview of the features, models, and classifiers derived from these areas that are the basis for modern automatic speaker recognition systems. We describe the components of state-of-the-art automatic speaker recognition systems, discuss application considerations and provide a brief survey of accuracy for different tasks.

This work was sponsored by the Department of Justice under Air Force Contract FA8721-05-C-0002. Opinions, interpretations, conclusions, and recommendations are those of the authors and are not necessarily endorsed by the United States Government.

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Authors and Affiliations

  1. Massachusetts Institute of Technology, Lincoln Laboratory, 244 Wood Street, Lexington, MA 02420, USA

    D. E. Sturim, W. M. Campbell & D. A. Reynolds

Authors
  1. D. E. Sturim
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  2. W. M. Campbell
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  3. D. A. Reynolds
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Christian Müller

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Sturim, D.E., Campbell, W.M., Reynolds, D.A. (2007). Classification Methods for Speaker Recognition. In: Müller, C. (eds) Speaker Classification I. Lecture Notes in Computer Science(), vol 4343. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74200-5_16

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  • DOI: https://doi.org/10.1007/978-3-540-74200-5_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74186-2

  • Online ISBN: 978-3-540-74200-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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