BERTraffic: BERT-based Joint Speaker Role and Speaker Change Detection for Air Traffic Control Communications
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F23%3APU149419" target="_blank" >RIV/00216305:26230/23:PU149419 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/10022718" target="_blank" >https://ieeexplore.ieee.org/document/10022718</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/SLT54892.2023.10022718" target="_blank" >10.1109/SLT54892.2023.10022718</a>
Alternative languages
Result language
angličtina
Original language name
BERTraffic: BERT-based Joint Speaker Role and Speaker Change Detection for Air Traffic Control Communications
Original language description
Automatic speech recognition (ASR) allows transcribing the communications between air traffic controllers (ATCOs) and aircraft pilots. The transcriptions are used later to extract ATC named entities, e.g., aircraft callsigns. One common challenge is speech activity detection (SAD) and speaker diarization (SD). In the failure condition, two or more segments remain in the same recording, jeopardizing the overall performance. We propose a system that combines SAD and a BERT model to perform speaker change detection and speaker role detection (SRD) by chunking ASR transcripts, i.e., SD with a defined number of speakers together with SRD. The proposed model is evaluated on real-life public ATC databases. Our BERT SD model baseline reaches up to 10% and 20% token-based Jaccard error rate (JER) in public and private ATC databases. We also achieved relative improvements of 32% and 7.7% in JERs and SD error rate (DER), respectively, compared to VBx, a well-known SD system.1
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
R - Projekt Ramcoveho programu EK
Others
Publication year
2023
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
IEEE Spoken Language Technology Workshop, SLT 2022 - Proceedings
ISBN
978-1-6654-7189-3
ISSN
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e-ISSN
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Number of pages
8
Pages from-to
633-640
Publisher name
IEEE Signal Processing Society
Place of publication
Doha
Event location
Doha
Event date
Jan 9, 2023
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000968851900086