A dynamic oscillator-bused model of the sequencing of phonemes in speech pr
oduction (OSCAR) is described. An analysis of phoneme movement errors (anti
cipations, perseverations, and exchanges) from a large naturalistic speech
error corpus provides a new set of data suitable for quantitative modeling
and is used to derive a set of constraints that any speech-production model
must address. The new computational model is shown to account for error ty
pe proportions, movement error distance gradients, the syllable-position ef
fect, and phonological similarity effects. The model provides an alternativ
e to frame-based accounts, serial buffer accounts, and associative chaining
theories of serial order processing in speech. (C) 2000 Academic Press.