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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.

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

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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