• DocumentCode
    3630079
  • Title

    Phoneme Recognition as a Member of Predefined Class using Hybrid Cascaded LVQ/Elman Neural Network

  • Author

    Zikrija Avdagic;Adnan Nuhic;Samim Konjicija

  • Author_Institution
    Faculty of Electrical Engineering of University of Sarajevo. zikrija.avdagic@etf.unsa.ba
  • fYear
    2007
  • Firstpage
    1195
  • Lastpage
    1198
  • Abstract
    What is presented is a new approach for implementing Bosnian phoneme recognition. While most of the literature on phoneme recognition is based on hidden Markov models (HMM), or on the recognition by neural networks (NN) of one type, the present system is implemented by hybrid cascaded LVQ/Elman NN. This model was created, because we noted that some types of NN achieve better recognition rate for some phonemes, while the other types of NN better recognize other phonemes. Presented system uses LVQ NN as a front-end recognizer, and depending on the obtained output, makes the re-recognition of the same phoneme by Elman NN. This system achieved higher recognition accuracy then standalone NN models.
  • Keywords
    "Neural networks","Hidden Markov models","Speech recognition","Speech processing","Finite impulse response filter","Signal processing","Cepstral analysis","Facial animation","Acoustic testing","Automatic speech recognition"
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Communications, 2007. ICSPC 2007. IEEE International Conference on
  • Print_ISBN
    978-1-4244-1235-8
  • Type

    conf

  • DOI
    10.1109/ICSPC.2007.4728539
  • Filename
    4728539