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Prediction and Extraction of Tower Controller Commands for Speech Recognition Applications

Ohneiser, Oliver and Helmke, Hartmut and Shetty, Shruthi and Kleinert, Matthias and Ehr, Heiko and Murauskas, Sarunas and Pagirys, Tomas (2021) Prediction and Extraction of Tower Controller Commands for Speech Recognition Applications. Journal of Air Transport Management, 95. Elsevier. doi: 10.1016/j.jairtraman.2021.102089. ISSN 0969-6997.

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Official URL: https://www.sciencedirect.com/science/article/abs/pii/S0969699721000727?via%3Dihub

Abstract

Air traffic controllers' (ATCos) workload often is a limiting factor for air traffic capacity. Thus, electronic support systems intend to reduce ATCos' workload. Automatic speech recognition can extract controller command elements from verbal clearances to deliver automatic input for air traffic control systems, thereby avoiding manual input. Assistant Based Speech Recognition (ABSR) with high command recognition rates and low error rates has proven to dramatically reduce ATCos' workload and increase capacity in approach scenarios. However, ABSR needs accurate hypotheses on expected commands and accurate extractions of command annotations from utterance transcriptions to achieve the required performance. Based on the experience of implementation for approach control, a hypotheses generator and a command extractor have been developed for speech recognition applications regarding tower control communication to face current and future challenges in the aerodrome environment. Three human-in-the-loop multiple remote tower simulation studies were performed with 16 ATCos from Hungary, Lithuania, and Finland at DLR Braunschweig from 2017 to 2019. Roughly 100 h of speech with corresponding radar data were recorded. Around 6000 speech utterances resulting in 16,000 commands have been manually transcribed and annotated. Some parts of the data have been used for training prediction models and command extraction algorithms. Other parts were used for evaluation of command prediction and command extraction. The automatic command extractor achieved a command extraction rate of 96.7%. The hypotheses generator showed operational feasibility with a sufficiently low command prediction error rate of 7.3%.

Item URL in elib:https://elib.dlr.de/143891/
Document Type:Article
Title:Prediction and Extraction of Tower Controller Commands for Speech Recognition Applications
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Ohneiser, OliverUNSPECIFIEDhttps://orcid.org/0000-0002-5411-691XUNSPECIFIED
Helmke, HartmutUNSPECIFIEDhttps://orcid.org/0000-0002-1939-0200UNSPECIFIED
Shetty, ShruthiUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Kleinert, MatthiasUNSPECIFIEDhttps://orcid.org/0000-0002-0782-4147UNSPECIFIED
Ehr, HeikoUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Murauskas, SarunasOro Navigacija (ON)UNSPECIFIEDUNSPECIFIED
Pagirys, TomasOro Navigacija (ON)UNSPECIFIEDUNSPECIFIED
Date:7 June 2021
Journal or Publication Title:Journal of Air Transport Management
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:Yes
In ISI Web of Science:Yes
Volume:95
DOI:10.1016/j.jairtraman.2021.102089
Publisher:Elsevier
Series Name:Elsevier
ISSN:0969-6997
Status:Published
Keywords:Air traffic controller; Multiple remote tower commands; Command prediction; Command extraction; Assistant based speech recognition
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:Air Transportation and Impact
DLR - Research area:Aeronautics
DLR - Program:L AI - Air Transportation and Impact
DLR - Research theme (Project):L - Human Factors
Location: Braunschweig
Institutes and Institutions:Institute of Flight Guidance > Controller Assistance
Deposited By: Ohneiser, Oliver
Deposited On:14 Sep 2021 10:36
Last Modified:20 Oct 2023 08:02

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