Data-Driven Analysis of European Portuguese Nasal Vowel Dynamics in Bilabial Contexts

Abstract

European Portuguese (EP) is characterized by a large number of nasals encompassing five phonemic nasal vowels. One notable characteristic of these sounds is their dynamic nature, involving both oral and nasal gestures, which makes their study and characterization challenging. The study of nasal vowels, in particular, has been addressed using a wide range of technologies: early descriptions were based on acoustics and nasalance, later expanded with articulatory data obtained from EMA and real-time magnetic resonance (RT-MRI). While providing important results, these studies were limited by the discrete nature of the EMA-pellets, providing only a small grasp of the vocal tract; by the small time resolution of the MRI data; and by the small number of speakers. To tackle these limitations, and to take advantage of recent advances in RT-MRI allowing 50 fps, novel articulatory data has been acquired for 11 EP speakers. The work presented here explores the capabilities of recently proposed data-driven approaches to model articulatory data extracted from RT-MRI to assess their suitability for investigating the dynamic characteristics of nasal vowels. To this end, we explore vocal tract configurations over time, along with the coordination of velum and lip aperture in oral and nasal bilabial contexts for nasal vowels and oral congeners. Overall, the results show that both generalized additive mixed models (GAMMs) and functional linear mixed models (FLMMs) provide an elegant approach to tackle the data from multiple speakers. More specifically, we found oro-pharyngeal differences in the tongue configurations for low and mid nasal vowels: vowel track aperture was larger in the pharyngeal and smaller in the palatal region for the three non-high nasal vowels, providing evidence of a raised and more advanced tongue position of the nasal vowels. Even though this work is aimed at exploring the applicability of the methods, the outcomes already highlight interesting data for the dynamic characterization of EP nasal vowels.