ACRP Graduate Student Paper - Automatic Speech Recognition for Air Traffic Control Communications

A significant fraction of communications between air traffic controllers and pilots is through speech, via radio channels. Automatic transcription of air traffic control (ATC) communications has the potential to improve system safety, operational performance, conformance monitoring, and to enhance air traffic controller training. The authors present an automatic speech recognition model tailored to the ATC domain that can transcribe ATC voice to text. The transcribed text is used to extract operational information such as call-sign and runway number. The models are based on recent improvements in machine learning techniques for speech recognition and natural language processing. The authors evaluate the performance of the model on diverse datasets.

Language

  • English

Media Info

  • Media Type: Digital/other
  • Features: Figures; References; Tables;
  • Pagination: 19p

Subject/Index Terms

Filing Info

  • Accession Number: 01763712
  • Record Type: Publication
  • Report/Paper Numbers: TRBAM-21-00234
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 23 2020 11:09AM