Detail publikačního výsledku

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

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

Originální název

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

Anglický název

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

Druh

Stať ve sborníku v databázi WoS či Scopus

Originální abstrakt

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.

Anglický abstrakt

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.

Klíčová slova

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

Klíčová slova v angličtině

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

Autoři

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

Rok RIV

2023

Vydáno

27.05.2022

Nakladatel

IEEE Signal Processing Society

Místo

Singapore

ISBN

978-1-6654-0540-9

Kniha

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

Strany od

8357

Strany do

8361

Strany počet

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"
}

Dokumenty

blatt_icassp2022_Call-Sign_Recognition_and_Understanding_for_Noisy_Air-Traffic_Transcripts_Using_Surveillance_Information