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Generating Quizzes to Support Training on Quality Management and Assurance in Space Science and Engineering

International Conference on Natural Language Generation (INLG), 2022
7 October 2022
Andrés García-Silva
Cristian Berrío
José Manuél Gómez-Pérez
ArXiv (abs)PDFHTMLGithub
Main:2 Pages
1 Figures
Bibliography:1 Pages
3 Tables
Abstract

Quality management and assurance is key for space agencies to guarantee the success of space missions, which are high-risk and extremely costly. In this paper, we present a system to generate quizzes, a common resource to evaluate the effectiveness of training sessions, from documents about quality assurance procedures in the Space domain. Our system leverages state of the art auto-regressive models like T5 and BART to generate questions, and a RoBERTa model to extract answers for such questions, thus verifying their suitability.

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