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Automatic Generation and Semantic Grading of Esperanto Sentences in a Teaching Context

Eckhard Bick
University of Southern Denmark, Denmark

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Ingår i: 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, s. 10-19

NEALT Proceedings Series 39:2, s. 10-19

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Publicerad: 2019-09-30

ISBN: 978-91-7929-998-9

ISSN: 1650-3686 (tryckt), 1650-3740 (online)

Abstract

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.

Nyckelord

corpus- and parsing-based CALL, sentence generation, sentence grading, semantic sentence evaluation, Esperanto teaching, AWE

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