Corpus ID: 39355678

Assistant-Based Speech Recognition for ATM Applications

@inproceedings{Helmke2015AssistantBasedSR,
  title={Assistant-Based Speech Recognition for ATM Applications},
  author={Hartmut Helmke and J{\"u}rgen Rataj and Thorsten M{\"u}hlhausen and Oliver Ohneiser and Heiko Ehr and Matthias Kleinert and Youssef Oualil and Marc Schulder},
  year={2015}
}
—Situation awareness of today’s automation relies so far on sensor information, data bases and the information delivered by the operator using an appropriate user interface. Listening to the conversation of people is not addressed until today, but an asset in many working situations of teams. This paper shows that automatic speech recognition (ASR) integrating into air traffic management applications is an upcoming technology and is ready for use now. Apple’s Siri® or Google’s Voice Search® are… Expand
Assistant based speech recognition - another pair of eyes for the Arrival Manager
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TLDR
The MALORCA project used machine learning algorithms to provide a generic, cheap and effective approach for adaptation of Assistant Based Speech Recognition (ABSR), which was divided into conceptual modules that contain generic parts (building blocks) and domain specific models. Expand
Semi-supervised Adaptation of Assistant Based Speech Recognition Models for different Approach Areas
TLDR
MALORCA project developed an initial basic ABSR system and semi-automatically tailored its recognition models for both Prague and Vienna approaches by machine learning from automatically transcribed audio data. Expand
Reducing Controller Workload by Automatic Speech Recognition Assisted Radar Label Maintenance
Various new hardand software centered methods were recently implemented to replace paper flight strips through modern technical solutions. These solutions provide valuable information for other ATMExpand
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In the last few years, the Federal Aviation Administration (FAA) has been investigating the use of automatic speech recognition in safety monitoring capabilities, with an initial focus on the towerExpand
Increasing ATM Efficiency withAssistant Based Speech Recognition
TLDR
An ABSR validation study with eight air traffic controllers validates that ABSR does not just reduce controllers’ workload, which would already be a lot, but it significantly increases ATM efficiency. Expand
Cost Reductions Enabled by Machine Learning in ATM How can Automatic Speech Recognition enrich human operators’ performance?
Various new solutions were recently implemented to replace paper flight strips through different means. Therefore, digital data comprising instructed air traffic controller (ATCO) commands can beExpand
A context-aware speech recognition and understanding system for air traffic control domain
TLDR
A multi-modal ASRU system, which dynamically integrates partial temporal and situational ATC context information to improve its performance and shows a relative reduction of the ATC command error rate metric. Expand
Machine Learning of Air Traffic Controller Command Extraction Models for Speech Recognition Applications
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An approach, which automatically learns a so-called Command Extraction Model from labelled controller utterances, which covers more than 98% of the commands and with just six hours of training data could achieve 94%. Expand
Real-time integration of dynamic context information for improving automatic speech recognition
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A real-time system which dynamically integrates situational context into ASR and achieves a 51% reduction of the Command Error Rate which is used as evaluation metric in the ATC domain. Expand
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