A dynamical model for generating prosodic structure

Abstract

The performance of the Monnin-Grosjean (MG) algorithm for predicting prosodic structure is compared with that of a system of dependency-grammar-based local markers (the DG system). Analyses of Brazilian Portuguese paragraphs read by five speakers reveal that the MG algorithm performs as well as the DG system when V-to-V normalised durations at word and phrase stress boundaries are used as indexes of prominence. These two procedures, however, have proved unsuccessful in dealing with individual variability. To overcome such a limitation, a dynamical model is proposed. By coupling syntactic and regularity constraints the main advantage of the model is the plausible simulation of speaker variability. Seven simulations were caried out by changing three model parameters: coupling strength, conditional probability of phrase stress placement, and V-to-V duration mean.