Implementing a Multi-lingual Chatbot for Positive Reinforcement in Young Learners
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
- Editors:
- Amittai Axelrod, Diyi Yang, Rossana Cunha, Samira Shaikh, Zeerak Waseem
- Venue:
- WiNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 91
- Language:
- URL:
- https://aclanthology.org/W19-3629
- DOI:
- Cite (ACL):
- Francisca Oladipo and Abdulmalik Rufai. 2019. Implementing a Multi-lingual Chatbot for Positive Reinforcement in Young Learners. In Proceedings of the 2019 Workshop on Widening NLP, page 91, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- Implementing a Multi-lingual Chatbot for Positive Reinforcement in Young Learners (Oladipo & Rufai, WiNLP 2019)