Eckhard Bick
University of Southern Denmark, Denmark
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Published in: Proceedings of the 8th Workshop on Natural Language Processing for Computer Assisted Language Learning (NLP4CALL 2019), September 30, Turku Finland
Linköping Electronic Conference Proceedings 164:2, p. 10-19
NEALT Proceedings Series 39:2, p. 10-19
Published: 2019-09-30
ISBN: 978-91-7929-998-9
ISSN: 1650-3686 (print), 1650-3740 (online)
This paper presents a method for the
automatic generation and semantic evaluation
of exercise sentences for Esperanto teaching.
Our sentence grader exploits both corpus data
and lexical resources (verb frames and
noun/adjective ontologies) to either generate
meaningful sentences from scratch, or to
determine the acceptability of a given input
sentence. Individual words receive scores for
how well they match the semantic conditions
projected onto their place in the syntactic
tree. In a CALL context, the system works
with a lesson-/level-constrained vocabulary
and can be integrated into e.g. substitution
table or slot filler exercises. While the
method as such is language-independent, we
also discuss how morphological clues
(affixes) can be exploited for semantic
purposes. When evaluated on out-of-corpus
course materials and short stories, the system
achieved a rejection precision, in terms of
false positives, of 98-99% at the sentence
level, and 93-97% at the word level.
corpus- and parsing-based CALL, sentence generation, sentence grading, semantic sentence evaluation, Esperanto teaching, AWE
