@inproceedings{garcia-silva-etal-2022-generating,
title = "Generating Quizzes to Support Training on Quality Management and Assurance in Space Science and Engineering",
author = "Garcia-Silva, Andres and
Berrio Aroca, Cristian and
Gomez-Perez, Jose Manuel and
Martinez, Jose and
Fleith, Patrick and
Scaglioni, Stefano",
editor = "Shaikh, Samira and
Ferreira, Thiago and
Stent, Amanda",
booktitle = "Proceedings of the 15th International Conference on Natural Language Generation: System Demonstrations",
month = jul,
year = "2022",
address = "Waterville, Maine, USA and virtual meeting",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.inlg-demos.2",
pages = "4--6",
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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<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.</abstract>
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%0 Conference Proceedings
%T Generating Quizzes to Support Training on Quality Management and Assurance in Space Science and Engineering
%A Garcia-Silva, Andres
%A Berrio Aroca, Cristian
%A Gomez-Perez, Jose Manuel
%A Martinez, Jose
%A Fleith, Patrick
%A Scaglioni, Stefano
%Y Shaikh, Samira
%Y Ferreira, Thiago
%Y Stent, Amanda
%S Proceedings of the 15th International Conference on Natural Language Generation: System Demonstrations
%D 2022
%8 July
%I Association for Computational Linguistics
%C Waterville, Maine, USA and virtual meeting
%F garcia-silva-etal-2022-generating
%X 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.
%U https://aclanthology.org/2022.inlg-demos.2
%P 4-6
Markdown (Informal)
[Generating Quizzes to Support Training on Quality Management and Assurance in Space Science and Engineering](https://aclanthology.org/2022.inlg-demos.2) (Garcia-Silva et al., INLG 2022)
ACL