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 [BibTeX] [Marc21]
Robust Command Recognition for Lithuanian Air Traffic Control Tower Utterances
Type of publication: Conference paper
Citation: Ohneiser_INTERSPEECH_2021
Publication status: Accepted
Booktitle: Interspeech
Year: 2021
Abstract: The maturity of automatic speech recognition (ASR) systems at controller working positions is currently a highly relevant technological topic in air traffic control (ATC). However, ATC service providers are less interested in pure word error rate (WER). They want to see benefits of ASR applications for ATC. Such applications transform recognized word sequences into semantic meanings, i.e., a number of related concepts such as callsign, type, value, unit, etc., which are combined to form commands. Digitized concepts or recognized commands can enter ATC systems based on an ontology for utterance annotation agreed between European ATC stakeholders. Command recognition (CR) has already been performed in approach control. However, spoken utterances of tower controllers are longer, include more free speech, and contain other command types than in approach. An automatic CR rate of 95.8% is achievable on perfect word recognition, i.e., manually transcribed audio recordings (gold transcriptions), taken from Lithuanian controllers in a multiple remote tower environment. This paper presents CR results for various speech-to-text models with different WERs on tower utterances. Although WERs were around 9%, we achieve CR rates of 85%. CR rates only slightly decrease with higher WERs, which enables to bring ASR applications closer to operational ATC environment.
Keywords: Air traffic control, command recognition rate, speech recognition, speech understanding, tower utterances
Projects HAAWAII
Authors Ohneiser, Oliver
Sarfjoo, Seyyed Saeed
Helmke, Hartmut
Shetty, Shruthi
Motlicek, Petr
Kleinert, Matthias
Ehr, heiko
Šarūnas Murauskas
Added by: [UNK]
Total mark: 0
  • Ohneiser_INTERSPEECH_2021.pdf