In the past, the nature of the compositional units proposed for spoken language has largely diverged from the types of control units pursued in the domains of other skilled motor tasks. A classic source of evidence as to the units structuring speech has been patterns observed in speech errors -"slips of the tongue". The present study reports, for the first time, on kinematic data from tongue and lip movements during speech errors elicited in the laboratory using a repetition task. Our data are consistent with the hypothesis that speech production results from the assembly of dynamically defined action units -gestures -in a linguistically structured environment. The experimental results support both the presence of gestural units and the dynamical properties of these units and their coordination. This study of speech articulation shows that it is possible to develop a principled account of spoken language within a more general theory of action.

This study systematically investigates the temporal organization of American English onset and coda consonant clusters on the basis of kinematic data. Results from seven speakers suggest that consonants in complex onsets are organized globally with respect to the following vowel, while consonants in complex codas are organized locally relative to the preceding vowel. These results support the competitive coupling model hypothesized for complex onsets, a model according to which consonant gestures in onsets are each coupled in-phase to the vowel, and antiphase with each other. The results are overall also consistent with the noncompetitive coupling relations assumed for codas, by which only the first consonant in a cluster is coupled antiphase with the vowel, and any subsequent consonants are coupled antiphase to each other. However, our data also show that the segmental composition of the cluster affects the timing relationship in codas, particularly /lC/ coda clusters pattern differently from other clusters and do not adhere to the predicted timing relations. The data contribute to our understanding of the interaction of linguistic structure and motor control of the articulators in speech production.

We propose an estimation approach to analyse correlated functional data which are observed on unequal grids or even sparsely. The model we use is a functional linear mixed model, a functional analogue of the linear mixed model. Estimation is based on dimension reduction via functional principal component analysis and on mixed model methodology. Our procedure allows the decomposition of the arXiv:1508.01686v1 [stat.ME] 7 Aug 2015 2 Jona Cederbaum et al.variability in the data as well as the estimation of mean effects of interest and borrows strength across curves. Confidence bands for mean effects can be constructed conditional on estimated principal components. We provide R-code implementing our approach. The method is motivated by and applied to data from speech production research.

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