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Tower Controller Command Prediction for Future Speech Recognition Applications

Ohneiser, Oliver and Helmke, Hartmut and Kleinert, Matthias and Siol, Gerald and Ehr, Heiko and Hobein, Stephanie and Predescu, Andrei-Vlad and Bauer, Jakob (2019) Tower Controller Command Prediction for Future Speech Recognition Applications. 9th SESAR Innovation Days, 02.-05. Dez. 2019, Athen, Griechenland.

Full text not available from this repository.

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 (ASR) can extract controller command elements from verbal clearances to deliver automatic air traffic control (ATC) system input and avoiding manual input. Assistant Based Speech Recognition (ABSR) systems with high command recognition rates and low error rates have proven to dramatically reduce ATCos' workload and increase capacity as an effect. However, those ABSR systems need accurate hypotheses about expected commands to achieve the necessary performance. Based on the experience with an ATC approach hypotheses generator, a prototypic tower command hypotheses generator (TCHG) was developed to face current and future challenges in the aerodrome environment. Two human-in-the-loop multiple remote tower simulation studies were performed with 13 ATCos from Hungary and Lithuania at DLR Braunschweig. Almost 40 hours of speech with corresponding radar data were recorded for training of the TCHG prediction models in 2017/2018. More than 45 hours of speech and radar data comprising roughly 4,600 voice utterances were recorded in the second simulation campaign for the TCHG evaluation test end of 2018. The TCHG showed operational feasibility with a sufficiently low command prediction error rate of down to 7.3% and low context portion predicted having a sufficiently fast command prediction frequency of once per 120ms to timely deliver the hypotheses to a speech recognition engine. Thus, the next step is to build an integrated ABSR system for the tower environment.

Item URL in elib:https://elib.dlr.de/130667/
Document Type:Conference or Workshop Item (Speech)
Title:Tower Controller Command Prediction for Future Speech Recognition Applications
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Ohneiser, OliverOliver.Ohneiser (at) dlr.dehttps://orcid.org/0000-0002-5411-691X
Helmke, HartmutHartmut.Helmke (at) dlr.deUNSPECIFIED
Kleinert, MatthiasMatthias.Kleinert (at) dlr.deUNSPECIFIED
Siol, Geraldgerald.siol (at) dlr.deUNSPECIFIED
Ehr, HeikoHeiko.Ehr (at) dlr.deUNSPECIFIED
Hobein, StephanieUNSPECIFIEDUNSPECIFIED
Predescu, Andrei-VladUNSPECIFIEDUNSPECIFIED
Bauer, JakobUNSPECIFIEDUNSPECIFIED
Date:2019
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:Air Traffic Controller; Tower Command Hypotheses Generator; Assistant Based Speech Recognition; Automatic Speech Recognition; PJ.16-04; Multiple Remote Tower
Event Title:9th SESAR Innovation Days
Event Location:Athen, Griechenland
Event Type:international Conference
Event Dates:02.-05. Dez. 2019
Organizer:EUROCONTROL
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Aeronautics
HGF - Program Themes:air traffic management and operations
DLR - Research area:Aeronautics
DLR - Program:L AO - Air Traffic Management and Operation
DLR - Research theme (Project):L - Efficient Flight Guidance
Location: Braunschweig
Institutes and Institutions:Institute of Flight Guidance > Controller Assistance
Deposited By: Ohneiser, Oliver
Deposited On:21 Nov 2019 09:34
Last Modified:16 Dec 2019 13:09

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