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 [BibTeX] [Marc21]
Automatic processing pipeline for collecting and annotating air-traffic voice communication data
Type of publication: Conference paper
Citation: Kocour_9THOPENSKYSYMPOSIUM2020_2021
Booktitle: Proceedings of 9th OpenSky Symposium 2020
Year: 2021
Month: November
Pages: 1-9
Publisher: MDPI
Location: Brussels, Belgium
Organization: OpenSky Network
Abstract: This document describes our pipeline for automatic processing of the ATCO -- pilot audio communication we developed as part of the ATCO2 project. So far we collected two thousand hours of audio recordings that we either pre-process for the transcribers or use the data for semi-supervised training. Both ways of using the collected data can further improve our pipeline by retraining our models. The proposed automatic processing pipeline is a cascade of many stand-alone components, namely: a) segmentation, b) volume control, c) signal-to-noise ratio filtering, d) diarization, e) 'speech-to-text' (ASR) module, f) English language detection, g) call-sign code recognition, h) ATCO -- pilot classification and i) highlighting the commands and values. %COMMAND_VALUE_REFERENCE The key component of the pipeline is a speech-to-text transcription system that has to be trained with the real-world ATC data, otherwise, the performance is poor. To further improve the speech-to-text performance, we apply both the semi-supervised training with our recordings, and the contextual adaptation that uses a list of plausible call-signs from surveillance data as auxiliary information. The downstream NLP/NLU tasks are important from the application point of view. These application tasks need accurate models operating on top of the real speech-to-text output, so there is a need for more data too. And creating the ATC data is the main aspiration of the ATCO$^2$ project. At the end of the project, the data will be packaged and distributed by ELDA.
Keywords: Air traffic control, Automatic Speech Recognition, Contextual Adaptation, language identification, named entity recognition, OpenSky Network
Projects Idiap
EC H2020- ATCO2
Authors Kocour, Martin
Vesely, Karel
Szoke, Igor
Kesiraju, Santosh
Juan, Zuluaga-Gomez.
Alexander, Blatt
Prasad, Amrutha
Iuliia, Nigmatulina
Motlicek, Petr
et al.
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Total mark: 0
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