elib
DLR-Header
DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

Machine Learning of Controller Command Prediction Models from Recorded Radar Data and Controller Speech Utterances

Kleinert, Matthias and Helmke, Hartmut and Siol, Gerald and Ehr, Heiko and Finke, Michael and Oualil, Youssef and Srinivasamurthy, Ajay (2017) Machine Learning of Controller Command Prediction Models from Recorded Radar Data and Controller Speech Utterances. 7th SESAR Innovation Days (SIDs), 2017-11-28 - 2017-11-30, Belgrad, Serbien.

Full text not available from this repository.

Abstract

Recently, the project AcListant® related to automatic speech recognition has achieved command recognition error rates below 1.7% based on Assistant Based Speech Recognition (ABSR). One main issue to transfer ABSR from the laboratory to the ops-rooms is its costs of deployment. Currently each ABSR model must manually be adapted to the local environment due to e.g. different accents and models to predict possible controller commands. The Horizon 2020 funded project MALORCA (Ma-chine Learning of Speech Recognition Models for Controller As-sistance) proposes a general, cheap and effective solution to au-tomate this re-learning, adaptation and customization process to new environments, by taking advantage of the large amount of speech data available in the ATM world. This paper presents an algorithm which automatically learns a model to predict control-ler commands from recorded untranscribed controller utterances and the corresponding radar data. The trained model is validated against transcribed controller commands for Vienna and Prague approach. Command error rates are reduced from 4.1% to 0.9% for Prague approach and from 10.9% to 2.0% for Vienna ap-proach.

Item URL in elib:https://elib.dlr.de/115564/
Document Type:Conference or Workshop Item (Speech)
Title:Machine Learning of Controller Command Prediction Models from Recorded Radar Data and Controller Speech Utterances
Authors:
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
Siol, GeraldUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Ehr, HeikoUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Finke, MichaelUNSPECIFIEDhttps://orcid.org/0000-0003-2355-7779UNSPECIFIED
Oualil, YoussefUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Srinivasamurthy, AjayUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Date:November 2017
Refereed publication:Yes
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
Page Range:pp. 1-8
Status:Published
Keywords:Machine Learning, Speech Recognition, Assistant Based Speech Recognition, Unsupervised Learning, Command Prediction Model, MALORCA
Event Title:7th SESAR Innovation Days (SIDs)
Event Location:Belgrad, Serbien
Event Type:international Conference
Event Start Date:28 November 2017
Event End Date:30 November 2017
Organizer:SESAR Joint Undertaking (SJU)
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:01 Dec 2017 09:12
Last Modified:24 Apr 2024 20:20

Repository Staff Only: item control page

Browse
Search
Help & Contact
Information
electronic library is running on EPrints 3.3.12
Website and database design: Copyright © German Aerospace Center (DLR). All rights reserved.