• DocumentCode
    3622341
  • Title

    Automatic Dialog Acts Recognition Based on Sentence Structure

  • Author

    P. Kral;C. Cerisara;J. Kleckova

  • Author_Institution
    LORIA UMR 7503, BP 239 - 54506 Vandoeuvre, France. kral@loria.fr
  • Volume
    1
  • fYear
    2006
  • fDate
    6/28/1905 12:00:00 AM
  • Abstract
    This paper deals with automatic dialog acts (DAs) recognition in Czech. Our work focuses on two applications: a multimodal reservation system and an animated talking head for hearing-impaired people. In that context, we consider the following DAs: statements, orders, investigation questions and other questions. The main goal of this paper is to propose, implement and evaluate new approaches to automatic DAs recognition based on sentence structure and prosody. Our system is tested on a Czech corpus that simulates a task of train tickets reservation. With lexical-only information, the classification accuracy is 91%. We proposed two methods to include sentence structure information, which respectively give 94% and 95%. When prosodic information is further considered, the recognition accuracy reaches 96%
  • Keywords
    "Hidden Markov models","Natural languages","Animation","Classification tree analysis","Bayesian methods","Informatics","Computer science","Application software","System testing","Speech"
  • Publisher
    ieee
  • Conference_Titel
    Acoustics, Speech and Signal Processing, 2006. ICASSP 2006 Proceedings. 2006 IEEE International Conference on
  • ISSN
    1520-6149
  • Print_ISBN
    1-4244-0469-X
  • Electronic_ISBN
    2379-190X
  • Type

    conf

  • DOI
    10.1109/ICASSP.2006.1659957
  • Filename
    1659957