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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" }
Documents
blatt_icassp2022_Call-Sign_Recognition_and_Understanding_for_Noisy_Air-Traffic_Transcripts_Using_Surveillance_Information.pdf