Analyzing time-varying spectral characteristics of speech with function-on-scalar regression

Journal of Phonetics, vol. 95, pp. 101191

Abstract

The acoustic characteristics of noise from fricatives and stop releases are difficult to analyze. The spectral characteristics of such noise are multi-dimensional, and popular methods for analyzing them typically rely on reducing this complex information to one or a few discrete numbers, such as spectral moments or coefficients of discrete cosine transformations. In this paper, I propose using function-on-scalar regression models as a method for analyzing and mass-comparing spectra with minimal reduction of the complexity in the signal. The method is further useful for analyzing how spectra change as a function of time. The usefulness of this method is demonstrated with a corpus analysis of Danish aspirated stop releases, using the DanPASS corpus. The analysis finds that /t/ releases are invariably affricated; /k/ releases are highly affected by coarticulatory context; and /p/ releases are almost always dominated by aspiration in the latter half of the release, but are affricated in the first half in certain contexts.

Authors 1

1. Rasmus Puggaard-Rode corresponding Aachen

   Leiden University

   Affiliation as printed

   Leiden University Centre for Linguistics, Netherlands