Skip to Main Content (Press Enter)

Logo UNIOR
  • ×
  • Home
  • Corsi
  • Insegnamenti
  • Persone
  • Strutture

UNIFIND
Logo UNIOR

|

UNIFIND

unior.it
  • ×
  • Home
  • Corsi
  • Insegnamenti
  • Persone
  • Strutture

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

Contributo in Atti di convegno
Data di Pubblicazione:
2019
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 ConceptNet 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.
Tipologia CRIS:
4.1 Contributo in Atti di convegno
Keywords:
ConceptNet, crowdsourcing, Language learning, Natural Language Processing
Elenco autori:
Sangati, Federico
Link alla scheda completa:
https://unora.unior.it/handle/11574/189342
Link al Full Text:
https://unora.unior.it//retrieve/handle/11574/189342/62799/RANLP_2019_Paper.pdf
Titolo del libro:
Proceedings of the International Conference Recent Advances in Natural Language Processing, RANLP 2019
  • Dati Generali

Dati Generali

URL

https://cognition.ouc.ac.cy/~chrodos/wp-content/uploads/2019/09/RANLP_2019_Paper.pdf
  • Utilizzo dei cookie

Realizzato con VIVO | Designed by Cineca | 26.5.0.0