Detecting English Speech in the Air Traffic Control Voice Communication
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F21%3APU142967" target="_blank" >RIV/00216305:26230/21:PU142967 - isvavai.cz</a>
Result on the web
<a href="https://www.isca-speech.org/archive/interspeech_2021/szoke21_interspeech.html" target="_blank" >https://www.isca-speech.org/archive/interspeech_2021/szoke21_interspeech.html</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.21437/Interspeech.2021-1033" target="_blank" >10.21437/Interspeech.2021-1033</a>
Alternative languages
Result language
angličtina
Original language name
Detecting English Speech in the Air Traffic Control Voice Communication
Original language description
Developing in-cockpit voice enabled applications require a realworld dataset with labels and annotations. We launched a community platform 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 processing pipeline. The proposed English Language Detection (ELD) system is based on the embeddings from Bayesian subspace multinomial model. It is trained on the word confusion network from an ASR system. It is robust, easy to train, and light weighted. We achieved 0:0439 equal-error-rate (EER), a 50% relative reduction as compared to the state-of-the-art acoustic ELD system based on x-vectors, in the in-domain scenario. Further, we achieved an EER of 0:1352, a 33% relative reduction as compared to the acoustic ELD, in the unseen language (out-of-domain) condition. We plan to publish the evaluation dataset from the ATCO2 project.
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
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings Interspeech 2021
ISBN
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ISSN
1990-9772
e-ISSN
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Number of pages
5
Pages from-to
3286-3290
Publisher name
International Speech Communication Association
Place of publication
Brno
Event location
Brno
Event date
Aug 30, 2021
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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