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Development and Integration of Speech Technology into COurseware for Language Learning: The DISCO Project

  • Helmer StrikEmail author
  • Joost van Doremalen
  • Jozef Colpaert
  • Catia Cucchiarini
Chapter
Part of the Theory and Applications of Natural Language Processing book series (NLP)

Abstract

Language learners seem to learn best in one-on-one interactive learning situations in which they receive optimal corrective feedback. However, providing this type of tutoring by trained language instructors is time-consuming and costly, and therefore not feasible for the majority of language learners. This particularly applies to oral proficiency, where corrective feedback has to be provided immediately after the utterance has been spoken, thus making it even more difficult to provide sufficient practice in the classroom. The recent appearance of Computer Assisted Language Learning (CALL) systems that make use of Automatic Speech Recognition (ASR) and other advanced automatic techniques offers new perspectives for practicing oral proficiency in a second language (L2). In the DISCO project a prototype of an ASR-based CALL application for practicing oral proficiency for Dutch as a second language (DL2) was developed. The application optimises learning through interaction in realistic communication situations and provides intelligent feedback on various aspects of DL2 speaking, viz. pronunciation, morphology and syntax. In this chapter we discuss the results of the DISCO project, we consider how DISCO has contributed to the state of the art and present some future perspectives.

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Copyright information

© The Author(s) 2013

Open Access. This chapter is distributed under the terms of the Creative Commons Attribution Noncommercial License, which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

Authors and Affiliations

  • Helmer Strik
    • 1
  • Joost van Doremalen
    • 1
  • Jozef Colpaert
    • 2
  • Catia Cucchiarini
    • 1
  1. 1.CLST, Radboud UniversityNijmegenThe Netherlands
  2. 2.Linguapolis, University of AntwerpenAntwerpBelgium

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