Comparing Two Smoothing Approaches in Estimating Kinematic Parameters.

PURPOSE: We compare two signal smoothing and differentiation approaches: a frequently used approach in the speech community of digital filtering with approximation of derivatives by finite differences and a spline smoothing approach widely used in other fields of human movement science. METHOD: In particular, we compare the values of a classic set of kinematic parameters estimated by the two smoothing approaches and assess, via regressions, how well these reconstructed values conform to known laws about relations between the parameters. RESULTS: Substantially smaller regression errors were observed for the spline smoothing than for the filtering approach. CONCLUSION: This result is in broad agreement with reports from other fields of movement science and underpins the superiority of splines also in the domain of speech.

How thresholding in segmentation affects the regression performance of the linear model.

Evaluating any model underlying the control of speech requires segmenting the continuous flow of speech effectors into sequences of movements. A virtually universal practice in this segmentation is to use a velocity-based threshold which identifies a movement onset or offset as the time at which the velocity of the relevant effector breaches some threshold percentage of the maximal velocity. Depending on the threshold choice, more or less of the movement's trajectory is left in for model regression. This paper makes explicit how the choice of this threshold modulates the regression performance of a dynamical model hypothesized to govern speech movements.

Fitts' Law in Tongue Movements of Repetitive Speech.

Fitts' law, perhaps the most celebrated law of human motor control, expresses a relation between the kinematic property of speed and the non-kinematic, task-specific property of accuracy. We aimed to assess whether speech movements obey this law using a metronome-driven speech elicitation paradigm with a systematic speech rate control. Specifically, using the paradigm of repetitive speech, we recorded via electromagnetic articulometry speech movement data in sequences of the form /CV…/ from 6 adult speakers. These sequences were spoken at 8 distinct rates ranging from extremely slow to extremely fast. Our results demonstrate, first, that the present paradigm of extensive metronome-driven manipulations satisfies the crucial prerequisites for evaluating Fitts' law in a subset of our elicited rates. Second, we uncover for the first time in speech evidence for Fitts' law at the faster rates and specifically beyond a participant-specific critical rate. We find no evidence for Fitts' law at the slowest metronome rates. Finally, we discuss implications of these results for models of speech.

The speed-curvature power law in tongue movements of repetitive speech.

The speed-curvature power law is a celebrated law of motor control expressing a relation between the kinematic property of speed and the geometric property of curvature. We aimed to assess whether speech movements obey this law just as movements from other domains do. We describe a metronome-driven speech elicitation paradigm designed to cover a wide range of speeds. We recorded via electromagnetic articulometry speech movements in sequences of the form /CV…/ from nine speakers (five German, four English) speaking at eight distinct rates. First, we demonstrate that the paradigm of metronome-driven manipulations results in speech movement data consistent with earlier reports on the kinematics of speech production. Second, analysis of our data in their full three-dimensions and using advanced numerical differentiation methods offers stronger evidence for the law than that reported in previous studies devoted to its assessment. Finally, we demonstrate the presence of a clear rate dependency of the power law's parameters. The robustness of the speed-curvature relation in our datasets lends further support to the hypothesis that the power law is a general feature of human movement. We place our results in the context of other work in movement control and consider implications for models of speech production.