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Cost Reductions Enabled by Machine Learning in ATM How can Automatic Speech Recognition enrich human operators performance?

Helmke, Hartmut and Kleinert, Matthias and Rataj, Jürgen and Motlicek, Petr and Klakow, Dietrich and Kern, Christian and Hlousek, Petr (2019) Cost Reductions Enabled by Machine Learning in ATM How can Automatic Speech Recognition enrich human operators performance? 13th USA/EUROPE Air Traffic Management R&D Seminar, 17.-21. June 2019, Wien, Österreich.

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Abstract

Various new solutions were recently implemented to replace paper flight strips through different means. Therefore, digital data comprising instructed air traffic controller (ATCO) commands can be used for various purposes. This paper summarizes recent works on developing speech recognition systems to automatically transcribe commands issued by airtraffic controllers to pilots allowing decrease of ATCOs’ workload, which leads to significant increase of ATM efficiency and cost savings. First experiments in AcListant® project have validated that Assistant Based Speech Recognition (ABSR) integrating a conventional speech recognizer with an assistant system can provide an adequate solution. The following EC H2020 funded MALORCA project has proposed new Machine Learning algorithms significantly reducing development and maintenance costs while exploiting new automatically transcribed speech corpora. In this paper, besides recapitulating achieved recognition performance for Prague and Vienna approach, new statistics obtained from various error analysis processes are presented. Results are detailed for different types of ATC commands followed by rationales causing the performance drops.

Item URL in elib:https://elib.dlr.de/130498/
Document Type:Conference or Workshop Item (Speech)
Title:Cost Reductions Enabled by Machine Learning in ATM How can Automatic Speech Recognition enrich human operators performance?
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Helmke, HartmutHartmut.Helmke. (at) dlr.deUNSPECIFIED
Kleinert, MatthiasMatthias.Kleinert (at) dlr.deUNSPECIFIED
Rataj, JürgenJuergen.Rataj (at) dlr.deUNSPECIFIED
Motlicek, PetrPetr.Motlicek (at) idiap.chUNSPECIFIED
Klakow, Dietrichdietrich.klakow (at) lsv.uni-saarland.deUNSPECIFIED
Kern, ChristianChristian.Kern (at) austrocontrol.atUNSPECIFIED
Hlousek, PetrPetr.Hlousek (at) ans.czUNSPECIFIED
Date:June 2019
Refereed publication:Yes
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:Machine Learning, Assistant Based Speech Recognition, Unsupervised Learning, Command Prediction Model, Automatic Speech Recognition, MALORCA, Annotation, Transcription
Event Title:13th USA/EUROPE Air Traffic Management R&D Seminar
Event Location:Wien, Österreich
Event Type:international Conference
Event Dates:17.-21. June 2019
Organizer:FAA / 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 Control > Controller Assistance
Deposited By: Diederich, Kerstin
Deposited On:15 Nov 2019 08:56
Last Modified:15 Nov 2019 08:56

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