Prediction of accent commands for the Fujisaki intonation model

Abstract

This paper presents a model to predict the accent commands (henceforth ACs) of the Fujisaki Model for the F0 contour, being known the phrase commands (henceforth FCs). Accent commands are associated with syllables. For each syllable, an artificial neural network (ANN) decides, with an accuracy of 89.4% whether there will be an associated AC or not. For syllables with associated AC, the amplitude, Aa, the onset time anticipation, T1a, and the offset time anticipation, T2a, are predicted by additional ANNs, with resulting linear correlation coefficient of 0.602, 0.743 and 0.650, respectively. The features used for each ANN are presented and discussed. Finally a comparison between target and predicted F0 contour is presented.