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    •   BracU IR
    • School of Engineering and Computer Science (SECS)
    • Department of Computer Science and Engineering (CSE)
    • Thesis & Report, BSc (Computer Science and Engineering)
    • View Item
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    Speech based gender identification using empirical mode decomposition (EMD)

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    10101036.pdf (799.4Kb)
    Date
    2014-04
    Publisher
    BRAC University
    Author
    Chowdhury, Mahpara Hyder
    Metadata
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    URI
    http://hdl.handle.net/10361/3225
    Abstract
    Traditionally for feature extraction, decomposition techniques such as Fourier decomposition are used to capture signals. But those methods have some margins like – it only works for linear and stationary data. On the other hand, in real world, we found data that are in non-linear and non-stationary. EMD or Empirical Mode Decomposition technique is a new approach introduced by Huang et al (1998) that can take any complicated signal and decomposed it to IMF. It extracts the amplitude and frequency information of a signal at a particular time. It is robust for non-linear and non-stationary signal processing. In this paper, I am using EMD as a new approach for gender identification based on speech signal. Gender identification based on the voice of a speaker consists of detecting if a speech signal is given by a male or female. Detecting the gender of a speaker has several applications.
    Keywords
    Computer science and engineering
    Description
    This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2014.
     
    Cataloged from PDF version of thesis report.
     
    Includes bibliographical references (page 36).
    Department
    Department of Computer Science and Engineering, BRAC University
    Collections
    • Thesis & Report, BSc (Computer Science and Engineering)

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