v-trel: Vocabulary Trainer for Tracing Word Relations - An Implicit Crowdsourcing Approach

Verena Lyding, Christos Rodosthenous, Federico Sangati, Umair ul Hassan, Lionel Nicolas, Alexander König, Jolita Horbacauskiene, Anisia Katinskaia


Abstract
In this paper, we present our work on developing a vocabulary trainer that uses exercises generated from language resources such as ConceptNet and crowdsources the responses of the learners to enrich the language resource. We performed an empirical evaluation of our approach with 60 non-native speakers over two days, which shows that new entries to expand Concept-Net can efficiently be gathered through vocabulary exercises on word relations. We also report on the feedback gathered from the users and an expert from language teaching, and discuss the potential of the vocabulary trainer application from the user and language learner perspective. The feedback suggests that v-trel has educational potential, while in its current state some shortcomings could be identified.
Anthology ID:
R19-1079
Volume:
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
Month:
September
Year:
2019
Address:
Varna, Bulgaria
Venue:
RANLP
SIG:
Publisher:
INCOMA Ltd.
Note:
Pages:
674–683
Language:
URL:
https://www.aclweb.org/anthology/R19-1079
DOI:
10.26615/978-954-452-056-4_079
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PDF:
http://aclanthology.lst.uni-saarland.de/R19-1079.pdf