Automatic statistical evaluation of quality of unit selection speech synthesis with different prosody manipulations

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F20%3A43958604" target="_blank" >RIV/49777513:23520/20:43958604 - isvavai.cz</a>
Result on the web
<a href="http://iris.elf.stuba.sk/JEEEC/data/pdf/2_120-02.pdf" target="_blank" >http://iris.elf.stuba.sk/JEEEC/data/pdf/2_120-02.pdf</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.2478/jee-2020-0012" target="_blank" >10.2478/jee-2020-0012</a>

Result language
angličtina
Original language name
Automatic statistical evaluation of quality of unit selection speech synthesis with different prosody manipulations
Original language description
Quality of speech synthesis is a crucial issue in comparison of various text-to-speech (TTS) systems. We proposed a system for automatic evaluation of speech quality by statistical analysis of temporal features (time duration, phrasing, and time structuring of an analysed sentence) together with standard spectral and prosodic features. This system was successfully tested on sentences produced by a unit selection speech synthesizer with a male as well as a female voice using two different approaches to prosody manipulation. Experiments have shown that for correct, sharp, and stable results all three types of speech features (spectral, prosodic, and temporal) are necessary. Furthermore, the number of used statistical parameters has a significant impact on the correctness and precision of the evaluated results. It was also demonstrated that the stability of the whole evaluation process is improved by enlarging the used speech material. Finally, the functionality of the proposed system was verified by comparison of the results with those of the standard listening test.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
—
OECD FORD branch
20205 - Automation and control systems

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

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