Text-to-Speech Application for Training of Aviation Radio Telephony Communication Operators

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F25%3AVRN2K6JD" target="_blank" >RIV/00216208:11320/25:VRN2K6JD - isvavai.cz</a>

Result on the web

<a href="https://www.scopus.com/record/display.uri?eid=2-s2.0-85210275185&origin=resultslist&sort=plf-f&src=s&sot=b&sdt=b&s=TITLE-ABS-KEY%28Text-to-Speech+Application+for+Training+of+Aviation+Radio+Telephony+Communication+Operators%29&relpos=0" target="_blank" >https://www.scopus.com/record/display.uri?eid=2-s2.0-85210275185&origin=resultslist&sort=plf-f&src=s&sot=b&sdt=b&s=TITLE-ABS-KEY%28Text-to-Speech+Application+for+Training+of+Aviation+Radio+Telephony+Communication+Operators%29&relpos=0</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/TAES.2024.3504493" target="_blank" >10.1109/TAES.2024.3504493</a>

Result language

angličtina

Original language name

Text-to-Speech Application for Training of Aviation Radio Telephony Communication Operators

Original language description

Air traffic controllers’ (ATCos) workload often is a limiting factor for air traffic capacity. Thus, electronic support systems intend to reduce ATCos’ workload. Automatic Speech Recognition (ASR) can extract controller command elements from verbal clearances to deliver automatic air traffic control (ATC) system input and avoiding manual input. Assistant Based Speech Recognition (ABSR) systems with high command recognition rates and low error rates have proven to dramatically reduce ATCos’ workload and increase capacity as an effect. However, those ABSR systems need accurate hypotheses about expected commands to achieve the necessary performance. Based on the experience with an ATC approach hypotheses generator, a prototypic tower command hypotheses generator (TCHG) was developed to face current and future challenges in the aerodrome environment. Two human-in-the-loop multiple remote tower simulation studies were performed with 13 ATCos from Hungary and Lithuania at DLR Braunschweig. Almost 40 hours of speech with corresponding radar data were recorded for training of the TCHG prediction models in 2017/2018. More than 45 hours of speech and radar data comprising roughly 4,600 voice utterances were recorded in the second simulation campaign for the TCHG evaluation test end of 2018. The TCHG showed operational feasibility with a sufficiently low command prediction error rate of down to 7.3% and low context portion predicted having a sufficiently fast command prediction frequency of once per 120ms to timely deliver the hypotheses to a speech recognition engine. Thus, the next step is to build an integrated ABSR system for the tower environment.

Czech name

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Czech description

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Type

J_SC - Article in a specialist periodical, which is included in the SCOPUS database

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)

Project

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Continuities

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Publication year

2024

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

IEEE Transactions on Aerospace and Electronic Systems

ISSN

0018-9251

e-ISSN

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Volume of the periodical

2024

Issue of the periodical within the volume

2024

Country of publishing house

US - UNITED STATES

Number of pages

21

Pages from-to

1-21

UT code for WoS article

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EID of the result in the Scopus database

2-s2.0-85210275185