Publication detail

Speech and Natural Language Processing Technologies for Pseudo-Pilot Simulator

PRASAD, A. ZULUAGA-GOMEZ, J. MOTLÍČEK, P. SARFJOO, S. NIGMATULINA, I. VESELÝ, K.

Original Title

Speech and Natural Language Processing Technologies for Pseudo-Pilot Simulator

Type

article in a collection out of WoS and Scopus

Language

English

Original Abstract

This paper describes a simple yet efficient repetition- based modular system for speeding up air-traffic controllers (ATCos) training. E.g., a human pilot is still required in EUROCONTROL's ESCAPE lite simulator https:// www.eurocontrol.int/simulator/escape during ATCo training. However, this need can be substituted by an automatic system that could act as a pilot. In this paper, we aim to develop and integrate a pseudo-pilot agent into the ATCo training pipeline by merging diverse artificial intelligence (AI) powered modules. The system understands the voice communications issued by the ATCo, and, in turn, it generates a spoken prompt that follows the pilot's phraseology to the initial communication. Our system mainly relies on open-source AI tools and air traffic control (ATC) databases, thus, proving its simplicity and ease of replicability. The overall pipeline is composed of the following: (1) a submodule that receives and pre-processes the input stream of raw audio, (2) an automatic speech recognition (ASR) system that transforms audio into a sequence of words; (3) a high-level ATC- related entity parser, which extracts relevant information from the communication, i.e., callsigns and commands, and finally, (4) a speech synthesizer submodule that generates responses based on the high-level ATC entities previously extracted. Overall, we show that this system could pave the way toward developing a real proof-of-concept pseudo-pilot system. Hence, speeding up the training of ATCos while drastically reducing its overall cost.

Keywords

Machine learning, air traffic controller training, air traffic management, BERT, automatic speech recognition, speech synthesi

Authors

PRASAD, A.; ZULUAGA-GOMEZ, J.; MOTLÍČEK, P.; SARFJOO, S.; NIGMATULINA, I.; VESELÝ, K.

Released

5. 12. 2022

Location

Budapest

Pages from

1

Pages to

9

Pages count

9

URL

https://arxiv.org/pdf/2212.07164.pdf

BibTex

@inproceedings{BUT185193,
  author="PRASAD, A. and ZULUAGA-GOMEZ, J. and MOTLÍČEK, P. and SARFJOO, S. and NIGMATULINA, I. and VESELÝ, K.",
  title="Speech and Natural Language Processing Technologies for Pseudo-Pilot Simulator",
  booktitle="Proceedings of the 12th SESAR Innovation Days",
  year="2022",
  pages="1--9",
  address="Budapest",
  doi="10.48550/arXiv.2212.07164",
  url="https://arxiv.org/pdf/2212.07164.pdf"
}