Lene Antonsen
University of Tromsø, Norway
Ryan Johnson
University of Tromsø, Norway
Trond Trosterud
University of Tromsø, Norway
Heli Uibo
University of Tromsø, Norway
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Published in: Proceedings of the second workshop on NLP for computer-assisted language learning at NODALIDA 2013; May 22-24; Oslo; Norway. NEALT Proceedings Series 17
Linköping Electronic Conference Proceedings 86:3, p. 27-38
NEALT Proceedings Series 17:3, p. 27-38
Published: 2013-05-17
ISBN: 978-91-7519-588-9
ISSN: 1650-3686 (print), 1650-3740 (online)
This paper presents an ICALL system for learning complex inflection systems; based upon finite state transducers (FST). Using a FST has several advantages: it makes it possible to generate a virtually unlimited set of exercises with a relatively small amount of work; and it makes it possible to process both input and output according to a wide range of parameters; such as dialect variation; and varying writing conventions. It also makes it possible to anticipate common error types; and give precise feedback both on errors and possible corrections. It shifts the developer’s focus from form generation and over to a pedagogically-motivated modelling of the learning task. The system is in active use on the web for two Saami languages; but can be made to work for any inflectional language.
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