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MALORCA SIGNED

Machine Learning of Speech Recognition Models for Controller Assistance

Total Cost €

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EC-Contrib. €

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Partnership

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 MALORCA project word cloud

Explore the words cloud of the MALORCA project. It provides you a very rough idea of what is the project "MALORCA" about.

automatic    misunderstandings    issue    pilots    combines    intensive    recognizer    machine    language    media    sensor    models    natural    causes    absr    creates    world    automate    voice    manual    learning    advantages    levels    accents    customisation    air    difference    generates    one    exchange    recognition    saarland    speech    never    capital    local    error    rooms    situation    cheap    standard    hampering    understand    transfer    re    proposes    replace    introduction    university    automation    search    acceptance    space    integral    usaar    advantage    data    deviations    below    environments    reduce    deployment    failures    command    algorithms    dlr    assumed    adapt    respective    traffic    controllers    ops    assistant    aclistant    rates    automated    phraseology    link    model    venture    operators    whereas    amount    automatically    reg       atm    solution    laboratory    time    sources    context    lack    environment    communication   

Project "MALORCA" data sheet

The following table provides information about the project.

Coordinator
DEUTSCHES ZENTRUM FUER LUFT - UND RAUMFAHRT EV 

Organization address
address: Linder Hoehe
city: KOELN
postcode: 51147
website: www.dlr.de

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Germany [DE]
 Project website http://www.malorca-project.de/
 Total cost 805˙587 €
 EC max contribution 538˙103 € (67%)
 Programme 1. H2020-EU.3.4.7.1 (Exploratory Research)
 Code Call H2020-SESAR-2015-1
 Funding Scheme SESAR-RIA
 Starting year 2016
 Duration (year-month-day) from 2016-04-01   to  2018-03-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    DEUTSCHES ZENTRUM FUER LUFT - UND RAUMFAHRT EV DE (KOELN) coordinator 211˙887.00
2    UNIVERSITAT DES SAARLANDES DE (SAARBRUCKEN) participant 187˙211.00
3    AUSTRO CONTROL OSTERREICHISCHE GESELLSCHAFT FUR ZIVILLUFTFAHRT MBH AT (WIEN) participant 86˙562.00
4    RIZENI LETOVEHO PROVOZU CESKE REPUBLIKY STATNI PODNIK CZ (JENEC) participant 52˙442.00
5    FONDATION DE L'INSTITUT DE RECHERCHE IDIAP CH (MARTIGNY) participant 0.00

Map

 Project objective

One of the main causes hampering the introduction of higher levels of automation in the Air Traffic Management (ATM) world is the intensive use of spoken language as the natural way of communication. Data link will be another media of communication with its known advantages compared to voice communication but for the future it is still assumed that data link communication will increase but never fully replace voice communication. Particularly for the time being controllers and pilots exchange information by spoken language, whereas automated systems understand the situation based only on sensor information. This difference in the end creates misunderstandings between operators and systems which lead to failures and further on to a lack of acceptance for automation. One promising solution is the introduction of automatic speech recognition as an integral part of automation. Recently, the venture capital funded project AcListant® has achieved command error rates below 2% based on Assistant Based Speech Recognition (ABSR), developed by Saarland University (USAAR) and DLR. ABSR combines speech recognition with an assistant system, which generates context information to reduce the search space of the speech recognizer. One main issue to transfer ABSR from the laboratory to the ops-rooms is its costs of deployment. Each ABSR model must manual adapted to the local environment due to e.g. different accents and deviations from standard phraseology. This project proposes a general, cheap and effective solution to automate this re-learning, adaptation and customisation process to new environments, taking advantage of the large amount of speech data available in the ATM world. Machine learning algorithms using these data sources will automatically adapt the ABSR models to the respective environment.

 Deliverables

List of deliverables.
System Requirement Document Documents, reports 2019-05-31 12:00:56
Report on Stakeholder Workshop Results Websites, patent fillings, videos etc. 2019-05-30 14:44:58
Gap Analysis Report (T0+24) Documents, reports 2019-05-30 14:44:56
Operational Concept Description Documents, reports 2019-05-30 14:44:56
Publishable Project Results final report Documents, reports 2019-05-30 14:44:54

Take a look to the deliverables list in detail:  detailed list of MALORCA deliverables.

 Publications

year authors and title journal last update
List of publications.
2017 Ajay Srinivasamurthy, Petr Motlicek, Ivan Himawan, Gyorgy Szaszak, Youssef Oualil, Hartmut Helmke
Semi-supervised Learning with Semantic Knowledge Extraction for Improved Speech Recognition in Air Traffic Control
published pages: , ISSN: , DOI:
2019-06-13
2017 M. Kleinert, H. Helmke, G. Siol, H. Ehr, M. Finke, Y. Oualil, A. Srinivasamurthy
Machine Learning of Controller Command Prediction Models from Recorded Radar Dataand Controller Speech Utterances
published pages: 8, ISSN: , DOI:
SESAR Innovation Days in Belgrade 2019-06-13
2017 Youssef Oualil, Dietrich Klakow, Gyorgy Szaszak, Ajay Srinivasamurthy, Hartmut Helmke, Petr Motlicek
A CONTEXT-AWARE SPEECH RECOGNITION AND UNDERSTANDING SYSTEM FOR AIR TRAFFIC CONTROL DOMAIN
published pages: , ISSN: , DOI:
Automatic Speech Recognition and Understanding Workshop 2019-06-13
2016 Hartmut Helmke, Petr Motlicek, Ivan Himawan, Oliver Ohneiser, Christian Windisch, Christian Kern, Aneta Cerna, Matej Nesvadba, Youssef Oualil, Dietrich Klakow, György Szaszak
MALORCA: Learning of Controllers\' Behaviour from Recorded Radar Data and Speech Utterances
published pages: , ISSN: , DOI:
6th SESAR INNOVATION DAYS 2019-06-13

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The information about "MALORCA" are provided by the European Opendata Portal: CORDIS opendata.

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