@inproceedings{lyding-etal-2019-v,
title = "v-trel: Vocabulary Trainer for Tracing Word Relations - An Implicit Crowdsourcing Approach",
author = {Lyding, Verena and
Rodosthenous, Christos and
Sangati, Federico and
ul Hassan, Umair and
Nicolas, Lionel and
K{\"o}nig, Alexander and
Horbacauskiene, Jolita and
Katinskaia, Anisia},
editor = "Mitkov, Ruslan and
Angelova, Galia",
booktitle = "Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)",
month = sep,
year = "2019",
address = "Varna, Bulgaria",
publisher = "INCOMA Ltd.",
url = "https://aclanthology.org/R19-1079",
doi = "10.26615/978-954-452-056-4_079",
pages = "674--683",
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.",
}
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%0 Conference Proceedings
%T v-trel: Vocabulary Trainer for Tracing Word Relations - An Implicit Crowdsourcing Approach
%A Lyding, Verena
%A Rodosthenous, Christos
%A Sangati, Federico
%A ul Hassan, Umair
%A Nicolas, Lionel
%A König, Alexander
%A Horbacauskiene, Jolita
%A Katinskaia, Anisia
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
%D 2019
%8 September
%I INCOMA Ltd.
%C Varna, Bulgaria
%F lyding-etal-2019-v
%X 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.
%R 10.26615/978-954-452-056-4_079
%U https://aclanthology.org/R19-1079
%U https://doi.org/10.26615/978-954-452-056-4_079
%P 674-683
Markdown (Informal)
[v-trel: Vocabulary Trainer for Tracing Word Relations - An Implicit Crowdsourcing Approach](https://aclanthology.org/R19-1079) (Lyding et al., RANLP 2019)
ACL
- Verena Lyding, Christos Rodosthenous, Federico Sangati, Umair ul Hassan, Lionel Nicolas, Alexander König, Jolita Horbacauskiene, and Anisia Katinskaia. 2019. v-trel: Vocabulary Trainer for Tracing Word Relations - An Implicit Crowdsourcing Approach. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019), pages 674–683, Varna, Bulgaria. INCOMA Ltd..