Anna Přibilová

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In the development of the voice conversion and the emotional speech style transformation in the text-to-speech systems, it is very important to obtain feedback information about the users’ opinion on the resulting synthetic speech quality. For this reason, the evaluations of the quality of the produced synthetic speech must often be performed for(More)
Autoregressive speech parameterization with and without preemphasis is discussed for the source-filter model and the harmonic model. Quality of synthetic speech is compared for the harmonic speech model using autoreg-ressive parameterization without preemphasis, with constant and adaptive preemphasis. Experimental results are evaluated by the RMS log(More)
The paper describes our experiment with using the Gaussian mixture models (GMM) for classification of speech uttered by a person wearing orthodontic appliances. For the GMM classification, the input feature vectors comprise the basic and the complementary spectral properties as well as the supra-segmental parameters. Dependence of classification correctness(More)
The paper is aimed at determination of formant features (FF) which describe vocal tract characteristics. It comprises analysis of the first three formant positions together with their bandwidths and the formant tilts. Subsequently , the statistical evaluation and comparison of the FF was performed. This experiment was realized with the speech material in(More)
In the development of the voice conversion and personification of the text-to-speech (TTS) systems, it is very necessary to have feedback information about the users' opinion on the resulting synthetic speech quality. Therefore, the main aim of the experiments described in this paper was to find out whether the classifier based on Gaussian mixture models(More)
This paper describes two experiments. The first one deals with evaluation of synthetic speech quality by reverse identification of original speakers whose voices had been used for several Czech text-to-speech (TTS) systems. The second experiment was aimed at evaluation of the influence of voice transformation on the original speaker recognition. The paper(More)
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