
handle: 11104/0004776
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.
metoda GUHA, neuronové sítě, syntéza řeči, klestění, modelování prosodie
metoda GUHA, neuronové sítě, syntéza řeči, klestění, modelování prosodie
| 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). | 0 | |
| 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. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
