Publication detail

Call-Sign Recognition and Understanding for Noisy Air-Traffic Transcripts Using Surveillance Information

BLATT, A. KOCOUR, M. VESELÝ, K. SZŐKE, I. KLAKOW, D.

Original Title

Call-Sign Recognition and Understanding for Noisy Air-Traffic Transcripts Using Surveillance Information

Type

conference paper

Language

English

Original Abstract

Air traffic control (ATC) relies on communication via speech between pilot and air-traffic controller (ATCO). The call-sign, as unique identifier for each flight, is used to address a specific pilot by the ATCO. Extracting the call-sign from the communication is a challenge because of the noisy ATC voice channel and the additional noise introduced by the receiver. A low signal-to-noise ratio (SNR) in the speech leads to high word error rate (WER) transcripts. We propose a new call-sign recognition and understanding (CRU) system that addresses this issue. The recognizer is trained to identify call-signs in noisy ATC transcripts and convert them into the standard International Civil Aviation Organization (ICAO) format. By incorporating surveillance information, we can multiply the call-sign accuracy (CSA) up to a factor of four. The introduced data augmentation adds additional performance on high WER transcripts and allows the adaptation of the model to unseen airspaces.

Keywords

Air Traffic Control, Call-sign Recognition, Context Incorporation, Data Augmentation

Authors

BLATT, A.; KOCOUR, M.; VESELÝ, K.; SZŐKE, I.; KLAKOW, D.

Released

27. 5. 2022

Publisher

IEEE Signal Processing Society

Location

Singapore

ISBN

978-1-6654-0540-9

Book

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Pages from

8357

Pages to

8361

Pages count

5

URL

https://ieeexplore.ieee.org/document/9746301

BibTex

@inproceedings{BUT178410,
  author="BLATT, A. and KOCOUR, M. and VESELÝ, K. and SZŐKE, I. and KLAKOW, D.",
  title="Call-Sign Recognition and Understanding for Noisy Air-Traffic Transcripts Using Surveillance Information",
  booktitle="ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
  year="2022",
  pages="8357--8361",
  publisher="IEEE Signal Processing Society",
  address="Singapore",
  doi="10.1109/ICASSP43922.2022.9746301",
  isbn="978-1-6654-0540-9",
  url="https://ieeexplore.ieee.org/document/9746301"
}