Generalized additive modeling to analyze dynamic phonetic data: a tutorial focusing on articulatory differences between L1 and L2 speakers of English

Abstract

In phonetics many data sets are encountered which deal with dynamic data collected over time. Examples include dynamic formant trajectories, or tongue position trajectories obtained via electromagnetic articulography. Traditional approaches to analyzing this type of data generally aggregate data over a certain timespan, or only include measurements at a certain fixed time point (e.g., formant measurements at the midpoint of a vowel). While these types of analyses are relatively easy to understand and conduct, I argue in this paper for a more elaborate approach, generalized additive modeling, which is able to take into account the non-linear patterns over time while simultaneously taking into account subject and item-related variability. I will illustrate its use in this tutorial using articulatory trajectories from L1 and L2 speakers of English. All data and R code is made available for readers to replicate the analysis presented in this paper.