Scipediacontent: Scipediacontent moved page Draft Content 158183016 to Helmke et al 2018a

2021-02-03T17:20:34Z

Scipediacontent moved page Draft Content 158183016 to Helmke et al 2018a

Scipediacontent: Created page with " == Abstract == Nowadays Automatic Speech Recognition (ASR) applications are increasingly successful in the air traffic (ATC) domain. Paramount to achieving this is collectin..."

2021-02-03T17:20:31Z

Created page with " == Abstract == Nowadays Automatic Speech Recognition (ASR) applications are increasingly successful in the air traffic (ATC) domain. Paramount to achieving this is collectin..."

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== Abstract ==

Nowadays Automatic Speech Recognition (ASR) applications are increasingly successful in the air traffic (ATC) domain. Paramount to achieving this is collecting enough data for speech recognition model training. Thousands of hours of ATC communication are recorded every day. However, the transcription of these data sets is resource intense, i.e. writing down the sequence of spoken words, and more importantly, interpreting the relevant semantics. Many different approaches including CPDLC (Controller Pilot Data Link Communications) currently exist in the ATC community for command transcription, a fact that e.g. complicates exchange of transcriptions. The partners of the SESAR funded solution PJ.16-04 are currently developing on a common ontology for transcription of controller-pilot communications, which will harmonize integration of ASR into controller working positions. The resulting ontology is presented in this paper.

== Original document ==

The different versions of the original document can be found in:

* [https://elib.dlr.de/123237/1/2018-10-01-PJ16-04-DASC-contribution-V-2-00.pdf https://elib.dlr.de/123237/1/2018-10-01-PJ16-04-DASC-contribution-V-2-00.pdf]

* [http://xplorestaging.ieee.org/ielx7/8540787/8569218/08569238.pdf?arnumber=8569238 http://xplorestaging.ieee.org/ielx7/8540787/8569218/08569238.pdf?arnumber=8569238],
: [http://dx.doi.org/10.1109/dasc.2018.8569238 http://dx.doi.org/10.1109/dasc.2018.8569238]

* [https://elib.dlr.de/123237 https://elib.dlr.de/123237],
: [https://academic.microsoft.com/#/detail/2904620939 https://academic.microsoft.com/#/detail/2904620939]

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Helmke et al 2018a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 158183016 to Helmke et al 2018a

Scipediacontent: Created page with " == Abstract == Nowadays Automatic Speech Recognition (ASR) applications are increasingly successful in the air traffic (ATC) domain. Paramount to achieving this is collectin..."