Semi-Supervised Training of DNN-Based Acoustic Model for ATC Speech Recognition
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F18%3A43952754" target="_blank" >RIV/49777513:23520/18:43952754 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007/978-3-319-99579-3_66" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-319-99579-3_66</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-99579-3_66" target="_blank" >10.1007/978-3-319-99579-3_66</a>
Alternative languages
Result language
angličtina
Original language name
Semi-Supervised Training of DNN-Based Acoustic Model for ATC Speech Recognition
Original language description
In this paper, we describe a semi-supervised training method used to generalize the Air Traffic Control (ATC) speech recognizer. The paper introduces the problems and challenges in ATC English recognition, describes available datasets and ongoing research projects. The baseline recognition model is then used to recognize the unlabelled data from a publicly available source. We used the LiveATC community portal which records and archives the recordings of ATC communication near the airports. The recognized unlabelled data are filtered using the data selection procedure based on confidence scores and the recognition acoustic model is retrained to obtain a more general model. The results on accented Czech and French data are reported.
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
20205 - Automation and control systems
Result continuities
Project
<a href="/en/project/TE01020197" target="_blank" >TE01020197: Centre for Applied Cybernetics 3</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Speech and Computer 20th International Conference, SPECOM 2018 Leipzig, Germany, September 18–22, 2018, Proceedings
ISBN
978-3-319-99578-6
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
10
Pages from-to
646-655
Publisher name
Springer Nature Switzerland AG
Place of publication
Cham
Event location
Leipzig, Germany
Event date
Sep 18, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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