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Dual-Pipeline Machine Learning Framework for Automated Interpretation of Pilot Communications at Non-Towered Airports

  • Abdullah All Tanvir
  • , Chenyu Huang
  • , Moe Alahmad
  • , Chuyang Yang
  • , Xin Zhong
  • University of Nebraska at Omaha
  • University of Nebraska Lincoln
  • Embry-Riddle Aeronautical University

Research output: Contribution to journalArticlepeer-review

Original languageEnglish
Article number32
JournalAerospace
Volume13
Issue number1
DOIs
StatePublished - Jan 2026
Externally publishedYes

ASJC Scopus Subject Areas

  • Aerospace Engineering

Keywords

  • Mel-spectrogram
  • air traffic automation
  • air traffic control
  • aircraft operations
  • audio classification
  • automatic speech recognition
  • aviation communication
  • data augmentation
  • deep learning
  • machine learning
  • non-towered airports

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