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Human Speaker Recognition Based Database Method

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Intelligent Systems Design and Applications (ISDA 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1351))

Abstract

During the last few years, many attempts were accomplished in the field of human sound and speech processing aiming to build speakers identification systems. The basic views of these systems were different, but the accuracy of the final computer process result for the identification depended on varieties of factors. For the intent of human sound extractions several methods in both the time domain and the frequency domain are used. Popular Linear Prediction Encoding (LPC) is used to parameterize voices, and to be used later in voiced/unvoiced separate extraction method functions. In comparison, direct classical methods are used for the extraction of human sound characteristics. Human voices are so much time varying that one recorded voice signal of a short time can never convey to distinguish speaker identification almost (100%).

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Author information

Authors and Affiliations

  1. College of Nursing, University of Kerbala, Kerbala, Iraq

    Ahmed Samit Hatem

  2. University of Information Technology and Communication, Baghdad, Iraq

    Muthanna J. Adulredhi & Ali M. Abdulrahman

  3. College of Computer Science and Information Technology, University of Sumer, Thi Qar, Rifai, Iraq

    Mohammed A. Fadhel

Authors
  1. Ahmed Samit Hatem
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  2. Muthanna J. Adulredhi
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  3. Ali M. Abdulrahman
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  4. Mohammed A. Fadhel
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Corresponding author

Correspondence to Mohammed A. Fadhel .

Editor information

Editors and Affiliations

  1. Scientific Network for Innovation and Research Excellence, Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Ajith Abraham

  2. Department of Computer Science, Università degli Studi di Milano, Milan, Milano, Italy

    Vincenzo Piuri

  3. Machine Intelligence Research Labs (MIR Labs), Auburn, WA, USA

    Niketa Gandhi

  4. Campus Centre de Créteil, Université Paris-Est Créteil, Créteil, France

    Patrick Siarry

  5. Department of Construction Management and Real Estate, Vilnius Gediminas Technical University, Vilnius, Lithuania

    Arturas Kaklauskas

  6. School of Engineering, Instituto Superior de Engenharia do Porto, Porto, Portugal

    Ana Madureira

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Hatem, A.S., Adulredhi, M.J., Abdulrahman, A.M., Fadhel, M.A. (2021). Human Speaker Recognition Based Database Method. In: Abraham, A., Piuri, V., Gandhi, N., Siarry, P., Kaklauskas, A., Madureira, A. (eds) Intelligent Systems Design and Applications. ISDA 2020. Advances in Intelligent Systems and Computing, vol 1351. Springer, Cham. https://doi.org/10.1007/978-3-030-71187-0_106

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