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The Airbus Air Traffic Control speech recognition 2018 challenge: towards ATC automatic transcription and call sign detection

Abstract : In this paper, we describe the outcomes of the challenge organized and run by Airbus and partners in 2018 on Air Traffic Control (ATC) speech recognition. The challenge consisted of two tasks applied to English ATC speech: 1) automatic speech-to-text transcription, 2) call sign detection (CSD). The registered participants were provided with 40 hours of speech along with manual transcriptions. Twenty-two teams submitted predictions on a five hour evaluation set. ATC speech processing is challenging for several reasons: high speech rate, foreign-accented speech with a great diversity of accents, noisy communication channels. The best ranked team achieved a 7.62% Word Error Rate and a 82.41% CSD F1-score. Transcribing pilots' speech was found to be twice as harder as controllers' speech. Remaining issues towards solving ATC ASR are also discussed in the paper.
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https://hal.archives-ouvertes.fr/hal-02419437
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Submitted on : Thursday, December 19, 2019 - 2:43:37 PM
Last modification on : Thursday, June 10, 2021 - 3:08:16 AM
Long-term archiving on: : Friday, March 20, 2020 - 5:28:27 PM

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  • HAL Id : hal-02419437, version 1
  • OATAO : 25003

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Thomas Pellegrini, Jérome Farinas, Estelle Delpech, François Lancelot. The Airbus Air Traffic Control speech recognition 2018 challenge: towards ATC automatic transcription and call sign detection. 20th Annual Conference of the International Speech Communication Association (INTERSPEECH 2019), Sep 2019, Graz, Austria. pp.2993-2997. ⟨hal-02419437⟩

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