A novel pitch decomposition method for the generalized linear alignment model

Superpositional models of intonation typically propose decomposing fundamental frequency (F 0 ) contours into phrase curves and accent curves, aligned with phrases and left-headed feet, respectively. Extracting these component curves from F 0 contours without making undue assumptions is challenging. We propose a novel method for decomposing pitch curves, based on the assumption that accent curves can be described by combining skewed normal distributions and sigmoid functions. In contrast to an earlier pitch decomposition algorithm (“PRISM”), this allows for simple joint optimization of phrase and accent curve parameters, using fewer parameters. The proposed method was evaluated on three speech corpora containing: (1) synthetically generated pitch curves, (2) all-sonorant utterances, and (3) utterances containing both sonorant and non-sonorant speech sounds. The root weighted mean squared error is small, and, on the corpus for which comparable data are available, is significantly smaller than for PRISM.