Publication detail

A Two-Step Approach to Leverage Contextual Data: Speech Recognition in Air-Traffic Communications

NIGMATULINA, I. ZULUAGA-GOMEZ, J. PRASAD, A. SARFJOO, S. MOTLÍČEK, P.

Original Title

A Two-Step Approach to Leverage Contextual Data: Speech Recognition in Air-Traffic Communications

Type

conference paper

Language

English

Original Abstract

Automatic Speech Recognition (ASR), as the assistance of speech communication between pilots and air-traffic controllers, can significantly reduce the complexity of the task and increase the reliability of transmitted information. ASR application can lead to a lower number of incidents caused by misunderstanding and improve air traffic management (ATM) efficiency. Evidently, high accuracy predictions, especially, of key information, i.e., callsigns and commands, are required to minimize the risk of errors. We prove that combining the benefits of ASR and Natural Language Processing (NLP) methods to make use of surveillance data (i.e. additional modality) helps to considerably improve the recognition of callsigns (named entity). In this paper, we investigate a two-step callsign boosting approach: (1) at the 1st step (ASR), weights of probable callsign n-grams are reduced in G.fst and/or in the decoding FST (lattices), (2) at the 2nd step (NLP), callsigns extracted from the improved recognition outputs with Named Entity Recognition (NER) are correlated with the surveillance data to select the most suitable one. Boosting callsign n-grams with the combination of ASR and NLP methods eventually leads up to 53.7% of an absolute, or 60.4% of a relative, improvement in callsign recognition.

Keywords

automatic speech recognition, human-computer interaction, Air-Traffic Control, Air-Surveillance Data, Callsign Detection, finite-state transducers

Authors

NIGMATULINA, I.; ZULUAGA-GOMEZ, J.; PRASAD, A.; SARFJOO, S.; MOTLÍČEK, P.

Released

27. 5. 2022

Publisher

IEEE Signal Processing Society

Location

Singapore

ISBN

978-1-6654-0540-9

Book

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Pages from

6282

Pages to

6286

Pages count

5

URL

https://ieeexplore.ieee.org/document/9746563

BibTex

@inproceedings{BUT178411,
  author="NIGMATULINA, I. and ZULUAGA-GOMEZ, J. and PRASAD, A. and SARFJOO, S. and MOTLÍČEK, P.",
  title="A Two-Step Approach to Leverage Contextual Data: Speech Recognition in Air-Traffic Communications",
  booktitle="ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings",
  year="2022",
  pages="6282--6286",
  publisher="IEEE Signal Processing Society",
  address="Singapore",
  doi="10.1109/ICASSP43922.2022.9746563",
  isbn="978-1-6654-0540-9",
  url="https://ieeexplore.ieee.org/document/9746563"
}

Documents

nigmatulina_icassp2022_A_Two-Step_Approach_to_Leverage_Contextual_Data_Speech_Recognition_in_Air-Traffic_Communications.pdf