Automatic Text-Independent Artifact Detection, Localization, and Classification in the Synthetic Speech

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F17%3A43932708" target="_blank" >RIV/49777513:23520/17:43932708 - isvavai.cz</a>

Result on the web

<a href="https://www.radioeng.cz/fulltexts/2017/17_04_1151_1160.pdf" target="_blank" >https://www.radioeng.cz/fulltexts/2017/17_04_1151_1160.pdf</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.13164/re.2017.1151" target="_blank" >10.13164/re.2017.1151</a>

Result language

angličtina

Original language name

Automatic Text-Independent Artifact Detection, Localization, and Classification in the Synthetic Speech

Original language description

The paper describes an experiment with statistical approaches to automatic detection, localization, and classification of the basic types of artifacts in the synthetic speech produced by the Czech text-to-speech system using the unit selection method. The aim of the first experiment is to detect the artifacts by the analysis of variances (ANOVA) and hypothesis testing. The second experiment is focused on localization of the detected artifacts by the Gaussian mixture models (GMM). Finally, the developed open-set artifact classifier is described. The influence of the length of the feature vector and its composition on the resulting artifact detection accuracy is also analyzed together with other factors affecting the stability of the artifact detection process. Further investigations have shown a relatively great influence of the number of mixtures and the type of a covariance matrix on the output artifact classification error rate as well as on the computational complexity. Results of the performed experiments confirm the functionality of the proposed artifact detector based on the ANOVA and hypothesis tests, and the GMM-based artifact localizer and classifier. The described statistical approaches represent the alternatives to the standard listening tests and the manual labeling of the artifacts.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

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OECD FORD branch

20205 - Automation and control systems

Project

<a href="/en/project/GA16-04420S" target="_blank" >GA16-04420S: Combining phonetic and corpus-based approaches to remedy disruptive effects in synthetic speech</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Radioengineering

ISSN

1210-2512

e-ISSN

—

Volume of the periodical

26

Issue of the periodical within the volume

4

Country of publishing house

CZ - CZECH REPUBLIC

Number of pages

10

Pages from-to

1151-1160

UT code for WoS article

000423270000032

EID of the result in the Scopus database

2-s2.0-85038078461