• DocumentCode
    271307
  • Title

    Using neural networks for a discriminant speech recognition system

  • Author

    ŞChiopu, Daniela ; Oprea, Mihaela

  • Author_Institution
    Pet.-Gas Univ. of Ploiesti, Ploieşti, Romania
  • fYear
    2014
  • fDate
    15-17 May 2014
  • Firstpage
    165
  • Lastpage
    169
  • Abstract
    The paper presents a case study of using neural networks for a discriminant automatic speech recognition system for the Romanian language. The uttered words by several speakers which the system must recognize can be commands for a robot. The study aims to examine the performance of the system by minimizing the error.
  • Keywords
    human-robot interaction; natural language processing; neural nets; speech recognition; Romanian language; discriminant automatic speech recognition system; human-computer interaction; neural networks; robot; speakers; Feature extraction; Hidden Markov models; Neural networks; Speech; Speech processing; Speech recognition; Training; feature extraction; multilayer perceptrons; recurrent neural networks; speech processing; speech recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Development and Application Systems (DAS), 2014 International Conference on
  • Conference_Location
    Suceava
  • Type

    conf

  • DOI
    10.1109/DAAS.2014.6842448
  • Filename
    6842448
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=271307