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Iterative Learning of Speech Recognition Models for Air Traffic Control

Srinivasamurthy, Ajay and Motlicek, Petr and Singh, Mittul and Oualil, Youssef and Kleinert, Matthias and Ehr, Heiko and Helmke, Hartmut (2018) Iterative Learning of Speech Recognition Models for Air Traffic Control. In: Interspeech. Interspeech 2018, 2018-09-02 - 2018-09-06, Hyderabad, India. doi: 10.21437/Interspeech.2018-1447.

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Automatic Speech Recognition (ASR) has recently proved to be a useful tool to reduce the workload of air traffic controllers leading to significant gains in operational efficiency. Air Traffic Control (ATC) systems in operation rooms around the world generate large amounts of untranscribed speech and radar data each day, which can be utilized to build and improve ASR models. In this paper, we propose an iterative approach that utilizes increasing amounts of untranscribed data to incrementally build the necessary ASR models for an ATC operational area. Our approach uses a semi-supervised learning framework to combine speech and radar data to iteratively update the acoustic model, language model and command prediction model (i.e. prediction of possible commands from radar data for a given air traffic situation) of an ASR system. Starting with seed models built with a limited amount of manually transcribed data, we simulate an operational scenario to adapt and improve the models through semi-supervised learning. Experiments on two independent ATC areas (Vienna and Prague) demonstrate the utility of our proposed methodology that can scale to operational environments with minimal manual effort for learning and adaptation.

Item URL in elib:https://elib.dlr.de/120924/
Document Type:Conference or Workshop Item (Speech)
Title:Iterative Learning of Speech Recognition Models for Air Traffic Control
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Kleinert, MatthiasUNSPECIFIEDhttps://orcid.org/0000-0002-0782-4147UNSPECIFIED
Helmke, HartmutUNSPECIFIEDhttps://orcid.org/0000-0002-1939-0200UNSPECIFIED
Date:September 2018
Journal or Publication Title:Interspeech
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In ISI Web of Science:No
Keywords:Speech recognition, Iterative learning, Semisupervised learning, Air traffic control
Event Title:Interspeech 2018
Event Location:Hyderabad, India
Event Type:international Conference
Event Start Date:2 September 2018
Event End Date:6 September 2018
Organizer:Indian Institute of Technology (IIT), Madras, India; International Speech Communication Association (ISCA)
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 (old)
Location: Braunschweig
Institutes and Institutions:Institute of Flight Guidance > Controller Assistance
Deposited By: Diederich, Kerstin
Deposited On:14 Nov 2018 09:27
Last Modified:24 Apr 2024 20:25

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