Artefact Determination by GMM-Based Continuous Detection of Emotional Changes in Synthetic Speech
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F19%3A43956317" target="_blank" >RIV/49777513:23520/19:43956317 - isvavai.cz</a>
Result on the web
<a href="https://ieeexplore.ieee.org/document/8768826" target="_blank" >https://ieeexplore.ieee.org/document/8768826</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/TSP.2019.8768826" target="_blank" >10.1109/TSP.2019.8768826</a>
Alternative languages
Result language
angličtina
Original language name
Artefact Determination by GMM-Based Continuous Detection of Emotional Changes in Synthetic Speech
Original language description
The paper is focused on a description of a system for automatic detection of speech artefacts based on the Gaussian mixture model (GMM) classifier. The system enables to detect one or more artefacts in synthetic speech produced by a text-to-speech system. Our speech artefact detection uses continual GMM classification of emotional states in 2-D affective space of valence and arousal within the whole sentence and calculates the final change in the evaluated emotions. The detected shift to negative emotions indicates presence of an artefact in the analysed sentence. The basic experiments confirm functionality of the developed system producing results with sufficient correctness of artefact detection. These results are comparable to those attained by a standard listening test method. Additional investigations show relatively great influence of the number of mixtures, the number of used emotional classes, and types of speech features on the evaluated emotional shift.
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/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)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
2019 42nd International Conference on Telecommunications and Signal Processing (TSP)
ISBN
978-1-72811-864-2
ISSN
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e-ISSN
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Number of pages
4
Pages from-to
45-48
Publisher name
IEEE
Place of publication
New York
Event location
Budapest, Hungary
Event date
Jul 1, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000493442800010