Advertisement

A Semantics-based communication system for dysphasic subjects

  • Pascal Vaillant
Natural Language and Terminology
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1211)

Abstract

Dysphasic subjects do not have complete linguistic abilities and only produce a weakly structured, topicalized language. They are offered artificial symbolic languages to help them communicate in a way more adapted to their linguistic abilities. After a structural analysis of a corpus of utterances from children with cerebral palsy, we define a semantic lexicon for such a symbolic language. We use it as the basis of a semantic analysis process able to retrieve an interpretation of the utterances. This semantic analyser is currently used in an application designed to convert iconic languages into natural language; it might find other uses in the field of language rehabilitation.

Keywords

Cerebral Palsy Semantic Relation Semantic Content Semantic Feature Semantic Network 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    C. K. Bliss. Semantography. 1965.Google Scholar
  2. 2.
    M. Covington. Parsing discontinuous constituents in dependency grammar. Computational Linguistics, 16(4): 234–236, 1990.Google Scholar
  3. 3.
    P. W. Demasco et K. F. McCoy. Generating text from compressed input: an intelligent interface for people with severe motor impairments. Communications of the ACM, 35(5): 68–78, 1992.Google Scholar
  4. 4.
    C.-L. Gérard, M. Dugas, et P. Lacert. Dysphasia and early focal brain injury. Hypothesis for postlesional cerebral reorganization. In First international symposium on specific speech and language disorders in children, University of Reading, U.K., 1987.Google Scholar
  5. 5.
    A. K. Joshi, L.S. Levy, et M. Takahashi. Tree adjunct grammars. Journal of Computer and System Sciences, 1975.Google Scholar
  6. 6.
    M. Kay. Unification. In M. Rosner et R. Johnson (eds), Computational Linguistics and Formal Semantics. Cambridge University Press, Cambridge, 1992.Google Scholar
  7. 7.
    L. L. Lloyd, R. W. Quist, et J. Windsor. A proposed Augmentative and Alternative Communication model. AAC Augmentative and Alternative Communication: 172–183, 1990.Google Scholar
  8. 8.
    F. Rastier. Sémantique Interprétative. Formes Sémiotiques. PUF, Paris, 1987.Google Scholar
  9. 9.
    Pascal Vaillant et Michaël Checler. Intelligent voice prosthesis: converting icons into natural language sentences. In Montpellier'95. 4th International Conference “Interface to Real & Virtual Worlds” Proceedings, Montpellier, 1995. EC2 & Cie, 9 rue Denis-Poisson, 75017 Paris-France.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1997

Authors and Affiliations

  • Pascal Vaillant
    • 1
  1. 1.Computer Science GroupThomson-CSF/LCROrsay cedexFrance

Personalised recommendations