• DocumentCode
    3644765
  • Title

    Real-time large vocabulary spontaneous speech recognition for spoken dialog systems

  • Author

    Jan Švec;Luboš Šmídl

  • Author_Institution
    Center of Applied Cybernetics, Department of Cybernetics, University of West Bohemia, Pilsen, Czech Republic
  • Volume
    5
  • fYear
    2011
  • Firstpage
    2431
  • Lastpage
    2436
  • Abstract
    This paper describes the method for modifying the baseline speech recognition system to be suitable for a use in spoken dialog system with mixed initiative and natural user´s input. We present three approaches for extending the recognition vocabulary to ensure the spoken dialog system is able to recognize all entities in the given domain. The colloquial text normalization method is proposed. The experiments performed on spontaneous speech corpus suggested that the proposed method is very important for languages where the formal written language and a common colloquial speech are very different. The overall word error rate was reduced by 16.7%.
  • Keywords
    "Vocabulary","Hidden Markov models","Speech recognition","Training data","Speech","Data models","History"
  • Publisher
    ieee
  • Conference_Titel
    Image and Signal Processing (CISP), 2011 4th International Congress on
  • Print_ISBN
    978-1-4244-9304-3
  • Type

    conf

  • DOI
    10.1109/CISP.2011.6100773
  • Filename
    6100773