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Real-Time Model for Automatic Vocal Emotion Recognition

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F08%3APU75434" target="_blank" >RIV/00216305:26220/08:PU75434 - isvavai.cz</a>

  • Result on the web

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

    Real-Time Model for Automatic Vocal Emotion Recognition

  • Original language description

    this paper deals with the task of vocal emotion recognition in real-time. For this aim, we introduced a simple model in the simulink environment based on the usage of mel bank coefficients as features and the GMM as a classifier. We made a comparison ofperformance of several preprocessing methods: MFCC, PLP, PCBF and MELB to find out which feature gives best classification results for four considered emotions: anger, happiness, sadness and neutral. We also made a comparison between two kinds of classifiers: Bayesian classifier based on Gaussian mixture models and artificial feed forward back propagation neural network.

  • Czech name

    Rozpoznání emočního stavu v reálném čase

  • Czech description

    this paper deals with the task of vocal emotion recognition in real-time. For this aim, we introduced a simple model in the simulink environment based on the usage of mel bank coefficients as features and the GMM as a classifier. We made a comparison ofperformance of several preprocessing methods: MFCC, PLP, PCBF and MELB to find out which feature gives best classification results for four considered emotions: anger, happiness, sadness and neutral. We also made a comparison between two kinds of classifiers: Bayesian classifier based on Gaussian mixture models and artificial feed forward back propagation neural network.

Classification

  • Type

    D - Article in proceedings

  • CEP classification

    JA - Electronics and optoelectronics

  • OECD FORD branch

Result continuities

  • Project

    <a href="/en/project/GA102%2F07%2F1303" target="_blank" >GA102/07/1303: Non-linear methods of speech enhancement</a><br>

  • Continuities

    Z - Vyzkumny zamer (s odkazem do CEZ)

Others

  • Publication year

    2008

  • Confidentiality

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

Data specific for result type

  • Article name in the collection

    Proceedings of 31th International Conference on Telecommunications and Signal Processing - TSP 2008

  • ISBN

    978-963-06-5487-6

  • ISSN

  • e-ISSN

  • Number of pages

    5

  • Pages from-to

  • Publisher name

    Neuveden

  • Place of publication

    Neuveden

  • Event location

    Parádfürdő

  • Event date

    Sep 3, 2008

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article