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Improved Context provided by Command Hypotheses Prediction, 2nd iteration

Helmke, Hartmut and Siol, Gerald (2017) Improved Context provided by Command Hypotheses Prediction, 2nd iteration. DLR-Interner Bericht. DLR-IB-FL-BS-2017-61. 49 S.

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Recently, the project AcListant® has achieved command error rates below 1.7 % for automatic speech recognition based on Assistant Based Speech Recognition (ABSR). It was validated that not only significant controller workload reductions were possible, but also significant improvement for ATM efficiency. 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 deviations from standard phraseology. MALORCA 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

Item URL in elib:https://elib.dlr.de/112491/
Document Type:Monograph (DLR-Interner Bericht)
Title:Improved Context provided by Command Hypotheses Prediction, 2nd iteration
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Date:May 2017
Refereed publication:No
Open Access:No
Number of Pages:49
Keywords:AcListant®; Assistant Based Speech Recognition; ABSR; Malorca
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:28 Jun 2017 14:55
Last Modified:28 Jun 2017 14:55

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