• DocumentCode
    3640862
  • Title

    A data-driven method for input feature selection within neural prosody generation

  • Author

    Çağlayan Erdem;Hans Georg Zimmermann

  • Author_Institution
    Dresden University of Technology, D-01062, Germany
  • Volume
    1
  • fYear
    2002
  • fDate
    5/1/2002 12:00:00 AM
  • Abstract
    The analysis and selection of input features within machine learning techniques is an important problem if a new system has to be established or the system has to be trained for a new task. Within a Text-to-Speech (ITS) application this task has to be handled while adapting a system to a new language or a new speaker.
  • Keywords
    "Artificial neural networks","Adaptation model","Data structures","Boolean functions","Training"
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech, and Signal Processing (ICASSP), 2002 IEEE International Conference on
  • ISSN
    1520-6149
  • Print_ISBN
    0-7803-7402-9
  • Type

    conf

  • DOI
    10.1109/ICASSP.2002.5743758
  • Filename
    5743758
    • Link To Document
    https://search.isc.ac/dl/search/defaultta.aspx?DTC=49&DC=3640862