The Speech Understanding and Dialog System Evar

  • H. Niemann
  • A. Brietzmann
  • R. Mühlfeld
  • P. Regel
  • G. Schukat
Part of the NATO ASI Series book series (volume 16)


This paper gives an overview of a research effort whose goal is to develop a system which can carry out a dialog concerning a particular task domain using continuous German speech for input and output. The main processing phases are initial segmentation and labeling, finding words, understanding the meaning and giving an answer. Specialized processing modules for handling these four phases were developed or are being developed. The processing modules communicate via a common database.


Automatic Speech Recognition Word Class Semantic Module Local Interpretation Phonological Rule 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    K. R. Popper, J. C. Eccles, “Das Ich und sein Gehirn,” R. Piper, München Zürich, P2.15 und E4.31, 1982.Google Scholar
  2. 2.
    A. Chapanis, “Interactive Human Communication,” Scient. American, 232, No. 3, 36–42, 1975.CrossRefGoogle Scholar
  3. 3.
    W. A. Lea (ed.), Trends in Speech Recognition, Prentice Hall, Englewood Cliffs, N. J., 1980.Google Scholar
  4. 4.
    D. H. Klatt, “Review of the ARPA Speech Understanding Project,” J. Acoustical Soc. of America, 62, 1345–1366, 1977.CrossRefGoogle Scholar
  5. 5.
    R. De Mori, “Recent Advances in Automatic Speech Recognition,” Proc. 4, Int. Joint Conf. Pattern Recognition, Kyoto, Japan, 106–124, 1978.Google Scholar
  6. 6.
    R. De Mori (ed.), Special Issue on Speech Understanding, Information Sciences.Google Scholar
  7. 7.
    L. Bahl, “Recognition of Isolated Word Sentences from a 5000-Word Vocabulary Office Correspondence Task,” Proc. ICASSP 83, Boston Mass., 1065, 1983.Google Scholar
  8. 8.
    T. Winograd, Language as a Cognitive Process, Vol. 1, Syntax, Addison Wesley, Rading Mass., 1983.MATHGoogle Scholar
  9. 9.
    H.-W. Hein, Das Erlanger Spracherkennungssystem, Dissertation Universität Erlangen-Nürnberg, Arbeitsberichte des IMMD Band 15, Nr. 15, Erlangen 1982.Google Scholar
  10. 10.
    H. Niemann, “The Erlangen System for Recognition and Understanding of Continuous German Speech,” in J. Nehmer (ed.), GI — 12. Jahrestagung, Informatik Fachberichte 57, Springer Berlin, Heidelberg, New York, 330–348, 1982.Google Scholar
  11. 11.
    P. Regel, “A Module for Acoustic-Phonetic Transcription of Fluently Spoken German Speech,” IEEE Trans. ASSP-30, 440–450, 1982.Google Scholar
  12. 12.
    P. Regel, Akustisch phonetische Transkription für die automatische Spracherkennung, Dissertation, in preparation.Google Scholar
  13. 13.
    S. B. Davis, P. Mermelstein, “Comparison of Parametric Representations for Monosyllabic Word Recognition in Continuously Spoken Sentences,” IEEE Trans. ASSP-28, 357–366, 1980.Google Scholar
  14. 14.
    J. Kittler, K. S. Fu, L. F. Pau, Pattern Recognition Theory and Applications, D. Reidel Publ. Comp., Dordrecht Boston London, 569, 1982.MATHGoogle Scholar
  15. 15.
    J. John, R. Mühlfeld, P. Regel, G. Siller, “Vergleich von Klassifikatoren für die Lauterkennung,” to appear in Proc. DAGM-84.Google Scholar
  16. 16.
    F. W. Kaeding (ed.), Häufigkeitswörterbuch der deutschen Sprache, Steglitz bei Berlin 1897–1898. We are grateful to Dr. Ruske who made available to us a tape with 8000 words.Google Scholar
  17. 17.
    D. W. Shipman, V. W. Zue, “Summary of Research in Speech Recognition,” Res. Lab. of Electronics, M.I.T., Cambridge Mass., 1982.Google Scholar
  18. 18.
    L. R. Bahl, F. Jelinek, “Decoding for Channels with Insertions, Deletions, and Substitutions with Applications to Speech Recognition,” IEEE Trans. IT-21, 404–411, 1975.Google Scholar
  19. 19.
    L. R. Bahl, F. Jelinek, R. L. Mercer, “A Maximum Likelihood Approach to Continuous Speech Recognition,” IEEE Trans. PAMI-5, 179–190, 1983.Google Scholar
  20. 20.
    A. R. Smith, Word Hypothesization in a Large-Vocabulary Speech Understanding System, Ph.D. Dissertation Dept. Computer Science, Carnegie Mellon University, Pittsburgh, PA, 1977.Google Scholar
  21. 21.
    H. Niemann, Pattern Analysis, Springer Series in Information Sciences 4, Springer, Berlin Heidelberg New York, 1981.MATHGoogle Scholar
  22. 22.
    R. J. Brachman, A Structural Paradigm for Representing Knowledge,Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1985

Authors and Affiliations

  • H. Niemann
    • 1
  • A. Brietzmann
    • 1
  • R. Mühlfeld
    • 1
  • P. Regel
    • 1
  • G. Schukat
    • 1
  1. 1.Lehrstuhl für Informatik 5 (Mustererkennung)Universität Erlangen-NürnbergErlangenWest Germany

Personalised recommendations