Linguistics

Philosophy

Neuroscience

Astrophysics

Variable (mathematics)

Computer science

Voice

Variation (astronomy)

Indexicality

Physics

Psychology

Mathematics

Vowel

Mathematical analysis

Perception

Speech recognition

Language Cognition and Neuroscience

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.

Structure in talker variability: How much is there and how much can it help?