Publication Details

Speech and Natural Language Processing Technologies for Pseudo-Pilot Simulator

PRASAD Amrutha, ZULUAGA-GOMEZ Juan, MOTLÍČEK Petr, SARFJOO Seyyed Saeed, NIGMATULINA Iuliia and VESELÝ Karel. Speech and Natural Language Processing Technologies for Pseudo-Pilot Simulator. In: Proceedings of the 12th SESAR Innovation Days. Budapest, 2022, pp. 1-9. Available from:
Czech title
Technologie zpracování řeči a přirozeného jazyka pro simulátor pseudopilota
conference paper
Prasad Amrutha (DCGM FIT BUT)
Zuluaga-Gomez Juan (IDIAP)
Motlíček Petr, Ing., Ph.D. (DCGM FIT BUT)
Sarfjoo Seyyed Saeed (IDIAP)
Nigmatulina Iuliia (IDIAP)
Veselý Karel, Ing., Ph.D. (DCGM FIT BUT)

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


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:// 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.

Proceedings of the 12th SESAR Innovation Days
12th SESAR Innovation Days, Budapešť, HU
Budapest, HU
   author = "Amrutha Prasad and Juan Zuluaga-Gomez and Petr Motl\'{i}\v{c}ek and Saeed Seyyed Sarfjoo and Iuliia Nigmatulina and Karel Vesel\'{y}",
   title = "Speech and Natural Language Processing Technologies for Pseudo-Pilot Simulator",
   pages = "1--9",
   booktitle = "Proceedings of the 12th SESAR Innovation Days",
   year = 2022,
   location = "Budapest, HU",
   language = "english",
   url = ""
Back to top