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Discrete Wavelet Transform for Automatic Speaker Recognition

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F10%3A00503960" target="_blank" >RIV/49777513:23520/10:00503960 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Discrete Wavelet Transform for Automatic Speaker Recognition

  • Original language description

    This paper deals with automatic speaker recognition. The main goal of this paper is to use and evaluate several Wavelet Transforms instead of the conventional parametrizations that are usually used as a parametrization method of automatic speaker recognition. Three discrete wavelet families with different number of coefficients have been used and evaluated: Daubechies, Symlets and Coiflets with two classifiers: Gaussian Mixture Model (GMM) and Multi-Layer Perceptron (MLP) on two Czech speaker corpora. We show that recognition accuracy of wavelet parametrizations is very good and sometimes outperform the best parametrizations that were presented in our previous work.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/2C06009" target="_blank" >2C06009: Complex knowledge base tools for natural language communication with the semantic web</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2010

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    CISP 2010, Vol. 7

  • ISBN

    978-1-4244-6514-9

  • ISSN

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

    3514-3518

  • Publisher name

    IEEE

  • Place of publication

    New York

  • Event location

    Yantai, China

  • Event date

    Oct 16, 2010

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article