Controlled Language Tools' and'Information Extraction Tools' for CALL Applications

  1. Paul Schmidt 1
  2. Sandrine Garnier 1
  3. Mike Sharwood 2
  4. Toni Badia 3
  5. Lourdes Díaz 3
  6. Martí Quixal 3
  7. Ana Ruggia 3
  8. Antonio S. Valderrabanos 4
  9. Alberto J. Cruz 4
  10. Enrique Torrejon 5
  11. Celia Rico 5
  12. Jorge Jimenez 5
  1. 1 IAI, Saarbrücken, Germany
  2. 2 Heriot-Watt University
    info

    Heriot-Watt University

    Edimburgo, Reino Unido

    ROR https://ror.org/04mghma93

  3. 3 Universitat Pompeu Fabra
    info

    Universitat Pompeu Fabra

    Barcelona, España

    ROR https://ror.org/04n0g0b29

  4. 4 SchlumbergerSema, Madrid, Spain
  5. 5 Universidad Europea de Madrid
    info

    Universidad Europea de Madrid

    Madrid, España

    ROR https://ror.org/04dp46240

Mostrar afiliaciones +
Actas:
Proceedings of InSTIL/ICALL2004 – NLP and Speech Technologies in Advanced Language Learning Systems

Año de publicación: 2004

Congreso: Symposium on Computer Assisted Learning. Venice, Italy. 17-19 June 2004

Tipo: Aportación congreso

GOOGLE SCHOLAR lock_openAcceso abierto editor

Resumen

his paper describes how mature NLP that has been successfully applied in the area of controlled language checking can be used to deliver intelligent CALL applications. It describes how an autonomous, longdistance 2nd language learning system for advanced learners can be created. The architecture of the system consists of a web-based multimodal user interface, skillspecific learning tools (reading, listening, speaking and writing tool), and a set of NLP-based evaluation tools. All modules are integrated in a flexible software architecture ensuring a user-friendly environment based on advanced concepts in language didactics. The thrust of the project is to show the potential of NLP for automatic evaluation of students’ productions.

Referencias bibliográficas

  • [1] Carl, Michael, Antje Schmidt-Wigger & Munpyo Hong (1997). KURD - A Formalism for Shallow Post Morphological Processing. Proc. of NLPRS'97.
  • [2] Hirst, G. J. and Budanitski, A. (2001). ‘Correcting Real-Word Spelling Errors by Restoring Lexical Cohesion’. In: ACL, Vol. 1, No. 1.
  • [3] Heringer, H.J. (2000). Fehlerlexikon. Aus Fehlern lernen: Beispiele und Diagnosen. Berlin, Cornelson Verlag.
  • [4] Kukich, K. (1992). Techniques for automatically correcting words in text. ACM Computing Surveys, 24: 377-439
  • [5] St-Onge, D. (1995). Detecting and correcting malapropisms with lexical chains, Master's thesis, Department of Computer Science, University of Toronto.