@inproceedings{7e8bf6ac3ffe489383fe566412f05e34,
title = "AI enabled tutor for accessible training",
abstract = "A significant number of jobs require highly skilled labor which necessitate training on pre-requisite knowledge. Examples include jobs in military, technical field such computer science, large scale fulfillment centers such as Amazon. Moreover, making such jobs accessible to the disabled population requires even more pre-requisite training such as knowledge of sign language. An artificial intelligent (AI) agent can potentially act as a tutor for such pre-requisite training. This will not only reduce resource requirements for such training but also decrease the time taken for making personnel job ready. In this paper, we develop an AI tutor that can teach users gestures that are required on the field as a pre-requisite. The AI tutor uses a model learning technique that learns the gestures performed by experts. It then uses a model comparison technique to compare a learner with the expert gesture and provides feedback for the learner to improve.",
keywords = "AI enabled tutor, ASL, Explainable AI",
author = "Ayan Banerjee and Imane Lamrani and Sameena Hossain and Prajwal Paudyal and Gupta, {Sandeep K.S.}",
note = "Publisher Copyright: {\textcopyright} Springer Nature Switzerland AG 2020. Copyright: Copyright 2020 Elsevier B.V., All rights reserved.; 21st International Conference on Artificial Intelligence in Education, AIED 2020 ; Conference date: 06-07-2020 Through 10-07-2020",
year = "2020",
doi = "10.1007/978-3-030-52237-7_3",
language = "English (US)",
isbn = "9783030522360",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer",
pages = "29--42",
editor = "Bittencourt, {Ig Ibert} and Mutlu Cukurova and Rose Luckin and Kasia Muldner and Eva Mill{\'a}n",
booktitle = "Artificial Intelligence in Education- 21st International Conference, AIED 2020, Proceedings, Part I",
}