Context-Aware XGBoost for Glottal Closure Instant Detection in Speech Signal

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F20%3A43959362" target="_blank" >RIV/49777513:23520/20:43959362 - isvavai.cz</a>
Result on the web
<a href="https://link.springer.com/chapter/10.1007%2F978-3-030-58323-1_48" target="_blank" >https://link.springer.com/chapter/10.1007%2F978-3-030-58323-1_48</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-58323-1_48" target="_blank" >10.1007/978-3-030-58323-1_48</a>

Result language
angličtina
Original language name
Context-Aware XGBoost for Glottal Closure Instant Detection in Speech Signal
Original language description
In this paper, we continue to investigate the use of classifiers for the automatic detection of glottal closure instants (GCIs) in the speech signal. We introduce context to extreme gradient boosting (XGBoost) and show that the context-aware XGBoost outperforms its context-free version. The proposed context-aware XGBoost is also shown to outperform traditionally used GCI detection algorithms on publicly available databases.
Czech name
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Czech description
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Project
<a href="/en/project/GA19-19324S" target="_blank" >GA19-19324S: Fully Trainable Deep Neural Network Based Czech Text-to-Speech Synthesis</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Text, Speech, and Dialogue 23rd International Conference, TSD 2020, Brno, Czech Republic, September 8-11, 2020, Proceedings
ISBN
978-3-030-58322-4
ISSN
0302-9743
e-ISSN
1611-3349
Number of pages
10
Pages from-to
446-455
Publisher name
Springer
Place of publication
Cham
Event location
Brno, Česká republika
Event date
Sep 8, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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