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Prosody Optimisation of a Czech Language Synthesizer

Authors: Tučková, J.; Šebesta, V. (Václav);

Prosody Optimisation of a Czech Language Synthesizer

Abstract

Each national language is described by specific grammatical rules. But rule-based knowledge representations alone cannot be used for the natural flow of speech. In this paper, optimisation of the naturalness of speech, i.e. the optimal choice of phonetic and phonologic parameters for prosody modelling is sought. We will try to find relevant features (speech parameters) having the basic influence on the fundamental frequency and duration of speech units. If the prosody of the synthesizer is controlled by an artificial neural network (ANN), optimisation of the ANN topology is necessary. The topology of the ANN is also dependent on the number of input neurons which represent the most important speech parameters. The pruning of the ANN based on the several approaches (GUHA method, sensitivities of the synaptic weights, etc.) is a suitable tool for reducing the ANN structure.

Country
Czech Republic
Related Organizations
Keywords

metoda GUHA, neuronové sítě, syntéza řeči, klestění, modelování prosodie

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green