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One aspect of the relationship between meaning and interaction is explored here by taking the English particle actually, which is characterized by flexibility of syntactic position, and investigating its use in a range of interactional contexts. Syntactic alternatives in the form of clause-initial or clause-final placement are found to be selected by reference to interactional exigencies. The temporally situated, contingent accomplishment of utterances in turns and their component turn-constructional units shows the emergence of meaning across a conversational sequence; it reveals syntactic flexibility as both a resource to be exploited for interactional ends and a constraint on that interaction.
In this chapter, we provide examples of how a DLM model can be pitted against human processing data, illustrating external validation (Chuang and Baayen, 2021). The first three examples address phenomena from phonetic realization: the acoustic duration of English s in pseudo-words, the spoken word duration of English homophones, and the vertical position of the tongue tip during the articulation of the [a] vowel in German. The second set of three examples takes a closer look at lexical decision latencies. One study looks deeper into the modelling of orthographic-semantic consistency (for English), a second study addresses trial-to-trial lexical learning in the course of a lexical decision megastudy (for Dutch), and the final study compares linear and deep learning (also for Dutch).