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QUANTIFYING THE BENEFITS OF SPEECH RECOGNITION FOR AN AIR TRAFFIC MANAGEMENT APPLICATION

Helmke, Hartmut and Oualil, Youssef and Schulder, Marc (2017) QUANTIFYING THE BENEFITS OF SPEECH RECOGNITION FOR AN AIR TRAFFIC MANAGEMENT APPLICATION. ESSV2017, 15.-17. März 2017, Saarbrücken, Deutschland.

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Abstract

Abstract: The project AcListant® (Active Listening Assistant), which uses automatic speech recognition to recognize the commands in air traffic controller to pilot communication, has achieved command recognition rates above 95%. These high rates were obtained with an Assistance-Based Speech Recognition (ABSR). An Arrival Manager (AMAN) cannot exactly predict the next actions of a controller, but it knows which commands are plausible in the current situation and which not. Therefore, the AMAN generates a set of possible commands every 20 seconds, which serves as context information for the speech recognizer. Different validation trials have been performed with controllers from Düsseldorf, Frankfurt, Munich, Prague and Vienna in DLR’s air traffic simulator in Braunschweig from 2014 to 2015. Decision makers of air navigation providers (ANSPs) are primary not interested in high recognition rates, respectively, low error rates. They are interested in reducing costs and efforts. Therefore, the validation trials, that were performed at the end of 2015, aimed at quantifying the benefits of using speech recognition with respect to both efficiency and controller workload. The paper describes the experiments performed to show that with ABSR support controller workload for radar label maintenance could be reduced by a factor of three and that ABSR enables fuel savings of 50 to 65 liters per flight

Item URL in elib:https://elib.dlr.de/111188/
Document Type:Conference or Workshop Item (Poster)
Title:QUANTIFYING THE BENEFITS OF SPEECH RECOGNITION FOR AN AIR TRAFFIC MANAGEMENT APPLICATION
Authors:
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Helmke, Hartmuthartmut.helmke (at) dlr.deUNSPECIFIED
Oualil, YoussefudsUNSPECIFIED
Schulder, MarcudsUNSPECIFIED
Date:2017
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Status:Published
Keywords:Active Listening Assistant; automatic speech recognition
Event Title:ESSV2017
Event Location:Saarbrücken, Deutschland
Event Type:international Conference
Event Dates:15.-17. März 2017
Organizer:Saarland University
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:27 Apr 2017 10:37
Last Modified:27 Apr 2017 10:37

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