Call-Sign Recognition and Understanding for Noisy Air-Traffic Transcripts Using Surveillance Information
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F22%3APU144937" target="_blank" >RIV/00216305:26230/22:PU144937 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/9746301" target="_blank" >https://ieeexplore.ieee.org/document/9746301</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/ICASSP43922.2022.9746301" target="_blank" >10.1109/ICASSP43922.2022.9746301</a>
Alternative languages
Result language
angličtina
Original language name
Call-Sign Recognition and Understanding for Noisy Air-Traffic Transcripts Using Surveillance Information
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
R - Projekt Ramcoveho programu EK
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISBN
978-1-6654-0540-9
ISSN
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e-ISSN
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Number of pages
5
Pages from-to
8357-8361
Publisher name
IEEE Signal Processing Society
Place of publication
Singapore
Event location
Singapore
Event date
May 22, 2022
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000864187908133