Detection of artefacts in czech synthetic speech based on ANOVA statistics

The paper describes an experiment with using the statistical approach based on analysis of variances (ANOVA) and hypothesis tests for detection of artefacts in the synthetic speech produced by the Czech text-to-speech system employing the unit selection principle. In addition, the paper analyses influence of different speech spectral features and supra-segmental parameters as well as the length of the feature vector on the resulting artefact detection accuracy. Other factors which can also have influence on stability of the artefact detection process are analysed, too. Obtained results of performed experiments confirm that the chosen concept works properly and the presented artefact detector can be used as an alternative to the standard listening tests.