Abstract
One of the persistent puzzles in understanding human speech perception is how listeners cope with talker variability. One thing that might help listeners is structure in talker variability: rather than varying randomly, talkers of the same gender, dialect, age, etc. tend to produce language in similar ways. Listeners are sensitive to this covariation between linguistic variation and socio-indexical variables. In this paper I present new techniques based on ideal observer models to quantify (1) the amount and type of structure in talker variation (informativity of a grouping variable), and (2) how useful such structure can be for robust speech recognition in the face of talker variability (the utility of a grouping variable). I demonstrate these techniques in two phonetic domains-word-initial stop voicing and vowel identity-and show that these domains have different amounts and types of talker variability, consistent with previous, impressionistic findings. An R package (phondisttools) accompanies this paper, and the source and data are available from osf.io/zv6e3.