Deep Learning and Online Speech Activity Detection for Czech Radio Broadcasting
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F18%3A43952599" target="_blank" >RIV/49777513:23520/18:43952599 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007%2F978-3-030-00794-2_46" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-030-00794-2_46</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-00794-2_46" target="_blank" >10.1007/978-3-030-00794-2_46</a>
Alternative languages
Result language
angličtina
Original language name
Deep Learning and Online Speech Activity Detection for Czech Radio Broadcasting
Original language description
In this paper, enhancements of online speech activity detection (SAD) is presented. Our proposed approach combines standard signal processing methods and modern deep-learning methods which allows simultaneous training of the detector’s parts that are usually trained or designed separately. In our SAD, an NN-based early score computation system, an NN-based score smoothing system and proposed online decoding system were incorporated in a training process. Besides the CNN and DNN, spectral flux and spectral variance features are also investigated. The proposed approach was tested on a Czech Radio broadcasting corpus. The corpus was used for investigation supervised and also semisupervised machine learning.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
20205 - Automation and control systems
Result continuities
Project
<a href="/en/project/EF15_003%2F0000466" target="_blank" >EF15_003/0000466: Artificial Intelligence and Reasoning</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
Text, Speech, and Dialogue 21st International Conference, TSD 2018, Brno, Czech Republic, September 11-14, 2018, Proceedings
ISBN
978-3-030-00793-5
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
8
Pages from-to
428-435
Publisher name
Springer Nature Switzerland AG
Place of publication
Cham
Event location
Brno, Czech Republic
Event date
Sep 11, 2018
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—