  Phonetics is the scientific field concerned with the study of how speech is
produced, heard and perceived. It abounds with data, such as acoustic speech
recordings, neuroimaging data, or articulatory data. In this paper, we provide
an introduction to different areas of phonetics (acoustic phonetics,
sociophonetics, speech perception, articulatory phonetics, speech inversion,
sound change, and speech technology), an overview of the statistical methods
for analyzing their data, and an introduction to the signal processing methods
commonly applied to speech recordings. A major transition in the statistical
modeling of phonetic data has been the shift from fixed effects to random
effects regression models, the modeling of curve data (for instance via GAMMs
or FDA methods), and the use of Bayesian methods. This shift has been driven in
part by the increased focus on large speech corpora in phonetics, which has
been driven by machine learning methods such as forced alignment. We conclude
by identifying opportunities for future research.
