Result Details

Detecting English Speech in the Air Traffic Control Voice Communication

SZŐKE, I.; KESIRAJU, S.; NOVOTNÝ, O.; KOCOUR, M.; VESELÝ, K.; ČERNOCKÝ, J. Detecting English Speech in the Air Traffic Control Voice Communication. In Proceedings Interspeech 2021. Proceedings of Interspeech. Brno: International Speech Communication Association, 2021. no. 8, p. 3286-3290. ISSN: 1990-9772.
Type
conference paper
Language
English
Authors
Szőke Igor, Ing., Ph.D., DCGM (FIT)
Kesiraju Santosh, Ph.D., DCGM (FIT)
Novotný Ondřej, Ing., Ph.D., DCGM (FIT)
Kocour Martin, Ing., DCGM (FIT)
Veselý Karel, Ing., Ph.D., DCGM (FIT)
Černocký Jan, prof. Dr. Ing., DCGM (FIT)
Abstract

Developing in-cockpit voice enabled applications require a realworlddataset with labels and annotations. We launched a communityplatform for collecting the Air-Traffic Control (ATC)speech, world-wide in the ATCO2 project. Filtering out non-English speech is one of the main components in the data processingpipeline. The proposed English Language Detection(ELD) system is based on the embeddings from Bayesian subspacemultinomial model. It is trained on the word confusionnetwork from an ASR system. It is robust, easy to train, andlight weighted. We achieved 0:0439 equal-error-rate (EER),a 50% relative reduction as compared to the state-of-the-artacoustic ELD system based on x-vectors, in the in-domain scenario.Further, we achieved an EER of 0:1352, a 33% relativereduction as compared to the acoustic ELD, in the unseen language(out-of-domain) condition. We plan to publish the evaluationdataset from the ATCO2 project.

Keywords

speech recognition, language detection, x-vectorextractor, acoustic model, air-traffic communication, data collection, text embeddings, Bayesian methods

URL
Published
2021
Pages
3286–3290
Journal
Proceedings of Interspeech, vol. 2021, no. 8, ISSN 1990-9772
Proceedings
Proceedings Interspeech 2021
Conference
Interspeech Conference
Publisher
International Speech Communication Association
Place
Brno
DOI
10.21437/Interspeech.2021-1033
UT WoS
000841879503076
EID Scopus
2-s2.0-85119510311
BibTeX 
@inproceedings{BUT175844,
  author="Igor {Szőke} and Santosh {Kesiraju} and Ondřej {Novotný} and Martin {Kocour} and Karel {Veselý} and Jan {Černocký}",
  title="Detecting English Speech in the Air Traffic Control Voice Communication",
  booktitle="Proceedings Interspeech 2021",
  year="2021",
  journal="Proceedings of Interspeech",
  volume="2021",
  number="8",
  pages="3286--3290",
  publisher="International Speech Communication Association",
  address="Brno",
  doi="10.21437/Interspeech.2021-1033",
  issn="1990-9772",
  url="https://www.isca-speech.org/archive/interspeech_2021/szoke21_interspeech.html"
}
Files
Projects
Automatic collection and processing of voice data from air-traffic communications, EU, Horizon 2020, start: 2019-11-01, end: 2022-02-28, completed
HAAWAII - Highly Automated Air Traffic Controller Workstations with Artificial Intelligence Integration, EU, Horizon 2020, H2020-SESAR-2019-2, start: 2020-06-01, end: 2022-11-30, completed
Research groups
Speech Data Mining Research Group BUT Speech@FIT (RG SPEECH)
Departments
Department of Computer Graphics and Multimedia (DCGM)
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