Detail publikace

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.

Originální název

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

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

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

Autoři

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

Vydáno

27. 5. 2022

Nakladatel

IEEE Signal Processing Society

Místo

Singapore

ISBN

978-1-6654-0540-9

Kniha

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

Strany od

6282

Strany do

6286

Strany počet

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"
}

Dokumenty

nigmatulina_icassp2022_A_Two-Step_Approach_to_Leverage_Contextual_Data_Speech_Recognition_in_Air-Traffic_Communications.pdf