A dynamic oscillator-based model of the sequencing of phonemes in speech production (OSCAR) is described. An analysis of phoneme movement errors (anticipations, 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 type proportions, movement error distance gradients, the syllable-position effect, and phonological similarity effects. The model provides an alternative to frame-based accounts, serial buffer accounts, and associative chaining theories of serial order processing in speech.
- Speech errors
- Speech production
ASJC Scopus subject areas
- Experimental and Cognitive Psychology
- Linguistics and Language