New rule-based and data-driven strategy to incorporate Fujisaki's F 0 model to a text-to-speech system in Castillian Spanish

We will present the analysis of a Spanish prosody database by estimating the parameters of Fujisaki's model for FO contours. These parameters are classified attending to linguistic features and they form the analysis database. When synthesizing FO contours we extract the linguistic features from the text and perform a k-Nearest Neighbour search. Linguistic feature comparison distance is trained using data from the prosody database. To avoid artifacts we perform a rule-base filtering on synthesis parameters. The results of our evaluation test show that the proposed system is significantly better than the previous neural network approach. This evaluation confirms the ability of Fujisaki's model to represent prosody information based on linguistic features.