Implementing a Multi-lingual Chatbot for Positive Reinforcement in Young Learners

Francisca Oladipo, Abdulmalik Rufai


Abstract
This is a humanitarian work –a counter-terrorism effort. The presentation describes the experiences of developing a multi-lingua, interactive chatbot trained on the corpus of two Nigerian Languages (Hausa and Fulfude), with simultaneous translation to a third (Kanuri), to stimulate conversations, deliver tailored contents to the users thereby aiding in the detection of the probability and degree of radicalization in young learners through data analysis of the games moves and vocabularies. As chatbots have the ability to simulate a human conversation based on rhetorical behavior, the system is able to learn the need of individual user through constant interaction and deliver tailored contents that promote good behavior in Hausa, Fulfulde and Kanuri languages.
Anthology ID:
W19-3629
Volume:
Proceedings of the 2019 Workshop on Widening NLP
Month:
August
Year:
2019
Address:
Florence, Italy
Venues:
ACL | WS | WiNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
91
Language:
URL:
https://www.aclweb.org/anthology/W19-3629
DOI:
Bib Export formats:
BibTeX MODS XML EndNote