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We propose a theory of how the speech gesture determines change in a functionally relevant variable of vocal tract state (e.g., constriction degree). A core postulate of the theory is that the gesture determines how the variable evolves in time independent of any executive timekeeper. That is, the theory involves intrinsic timing of speech gestures. We compare the theory against others in which an executive timekeeper determines change in vocal tract state. Theories that employ an executive timekeeper have been proposed to correct for disparities between theoretically predicted and experimentally observed velocity profiles. Such theories of extrinsic timing make the gesture a nonautonomous dynamical system. For a nonautonomous dynamical system, the change in state depends not just on the state but also on time. We show that this nonautonomous extension makes surprisingly weak kinematic predictions both qualitatively and quantitatively. We propose instead that the gesture is a theoretically simpler nonlinear autonomous dynamical system. For the proposed nonlinear autonomous dynamical system, the change in state depends nonlinearly on the state and does not depend on time. This new theory provides formal expression to the notion of intrinsic timing. Furthermore, it predicts experimentally observed relations among kinematic variables.
We offer a dynamical model of phonological planning that provides a formal instantiation of how the speech production and perception systems interact during online processing. The model is developed on the basis of evidence from an experimental task that requires concurrent use of both systems, the so-called response-distractor task in which speakers hear distractor syllables while they are preparing to produce required responses. The model formalizes how ongoing response planning is affected by perception and accounts for a range of results reported across previous studies. It does so by explicitly addressing the setting of parameter values in representations. The key unit of the model is that of the dynamic field, a distribution of activation over the range of values associated with each representational parameter. The setting of parameter values takes place by the attainment of a stable distribution of activation over the entire field, stable in the sense that it persists even after the response cue in the above experiments has been removed. This and other properties of representations that have been taken as axiomatic in previous work are derived by the dynamics of the proposed model. (C) 2016 Elsevier Inc. All rights reserved.