@article{ref1,
title="Automatic speech recognition in noise polluted cockpit environments for monitoring the approach briefing in commercial aviation",
journal="Proceedings of International Workshop on ATM/CNS",
year="2022",
author="Bollmann, Sven and Fullgraf, Jonas and Roxlau, Christian and Feuerle, Thomas and Hecker, Peter and Krishnan, Aravind and Ostermann, Simon and Klakow, Dietrich and Nicolas, Großmann and Stefan, Muller-Diveky",
volume="1",
number="",
pages="170-175",
abstract="The approach briefing is of major importance in commercial aviation. Conducted by the flight crew, it ensures a thorough and mutual understanding of the upcoming descent and approach phase. With regard to a future implementation of reduced crew operations (RCO), an AI-based system is currently being developed that is able to follow the spoken approach briefing, check for its completeness and inform the pilot about possibly missing items. This paper describes the language processing part of the overall system. A commercially available automatic speech recognition system is trained on aviation specific vocabulary and strategies for dealing with cockpit noise are discussed. Steps towards a possible certification of the system according to the European Union Aviation Safety Agency (EASA) Artificial Intelligence Roadmap are outlined.<p /> <p>Language: en</p>",
language="en",
issn="2758-1586",
doi="10.57358/iwac.1.0_170",
url="http://dx.doi.org/10.57358/iwac.1.0_170"
}