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Pattern Recognition Methods and Features Selection for Speech Emotion Recognition System

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27240%2F15%3A86090758" target="_blank" >RIV/61989100:27240/15:86090758 - isvavai.cz</a>

  • Alternative codes found

    RIV/61989100:27740/15:86090758

  • Result on the web

    <a href="http://www.hindawi.com/journals/tswj/2015/573068/" target="_blank" >http://www.hindawi.com/journals/tswj/2015/573068/</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1155/2015/573068" target="_blank" >10.1155/2015/573068</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Pattern Recognition Methods and Features Selection for Speech Emotion Recognition System

  • Original language description

    The impact of the classification method and features selection for the speech emotion recognition accuracy is discussed in this paper. Selecting the correct parameters in combination with the classifier is an important part of reducing the complexity ofsystem computing. This step is necessary especially for systems that will be deployed in real-time applications. The reason for the development and improvement of speech emotion recognition systems is wide usability in nowadays automatic voice controlledsystems. Berlin database of emotional recordings was used in this experiment. Classification accuracy of artificial neural networks, k-nearest neighbours, and Gaussian mixture model is measured considering the selection of prosodic, spectral, and voicequality features. The purpose was to find an optimal combination of methods and group of features for stress detection in human speech. The research contribution lies in the design of the speech emotion recognition system due to its accur

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

  • CEP classification

    IN - Informatics

  • OECD FORD branch

Result continuities

  • Project

  • Continuities

    S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2015

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    The Scientific World Journal

  • ISSN

    2356-6140

  • e-ISSN

  • Volume of the periodical

    2015

  • Issue of the periodical within the volume

    Neuveden

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    7

  • Pages from-to

    1-7

  • UT code for WoS article

  • EID of the result in the Scopus database

    2-s2.0-84939857445