Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP)
Sandhya Vidyashankar
Rakshit Vahi
Yash Karkhanis
Gowri Srinivasa
2021-11-30
<p>We present an automated, visual question answering based companion – Vis Quelle - to facilitate elementary learning of word-object associations. In particular, we attempt to harness the power of machine learning models for object recognition and the understanding of combined processing of images and text data from visual-question answering to provide variety and nuance in the images associated with letters or words presented to the elementary learner. We incorporate elements such as gamification to motivate the learner by recording scores, errors, etc., to track the learner’s progress. Translation is also provided to reinforce word-object associations in the user’s native tongue, if the learner is using Vis Quelle to learn a second language. Keywords: Visual question answering; object recognition; question generation; question answering; word-object association.</p>
https://doi.org/10.35940/ijitee.A9599.1111121
oai:zenodo.org:5726768
eng
Zenodo
issn:2278-3075
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
International Journal of Innovative Technology and Exploring Engineering (IJITEE), 11(1), 41-49, (2021-11-30)
Visual question answering; object recognition; question generation; question answering; word-object association.
Vis Quelle: Visual Question-based Elementary Learning Companion a system to Facilitate Learning Word-Object Associations
info:eu-repo/semantics/article