Cognitive linguistics (CL) has, in recent years, seen an increase in appeals to include multiple modalities in language analyses. While individual studies have incorporated gesture, gaze, facial expression, and prosody, among other modalities, CL has yet to completely embrace the systematic analysis of face-to-face interaction. Here, I present an investigation of five aspect-marking periphrastic constructions in North American English. Using naturalistic interactional data (n=250) from the Red Hen archive, this study establishes a multimodal profile for auxiliary constructions headed by one of five highly aspectualized verbs: continue, keep, start, stop, and quit, as in The jackpot continued to grow and He quit smoking. Results show that gesture timing, the structure of the gesture stroke, and gesture movement type, are variables that iconically and differentially represent distinctive aspectual conceptualizations. This study enhances our understanding of aspectual representation in co-speech gesture and informs the ongoing debate within CL and construction grammar circles of what constitutes conventionalization, or what constitutes a construction (mono- or multimodal).

We present a quantitative analysis of evaluative language in a genre in which it is particularly prominent, that of movie reviews. The data chosen are non-professional consumer-generated reviews written in English, German and Spanish. The reviews are analysed in terms of the categories of Attitude and Graduation within the Appraisal framework (Martin and White, 2005). A number of similarities in the distribution of the Appraisal subcategories were found across the three languages, such as the high frequency of Appreciation and the narrow relationship between the global polarity of the reviews and the individual polarity of the spans. More importantly, the analysis uncovers a number of cross-linguistic distributional differences, which may be explained in terms of a wide array of factors, such as lexicogrammar, word order, argumentative style or sociocultural reasons.

In this paper, I explore the linguistic and kinesic expression of contrast—the pitting of one position, object, or idea, against another. The archetype utterance for the embodied expression of contrast in English is the bipartite construction On the one hand . . . . On the other hand . . . . in which hand gestures are often performed sequentially along the sagittal axis (first on one side and then on the other side of the body) to depict the two options. However, English speakers have a variety of other linguistic means available to them for expressing contrast. Using data from naturally occurring discourse, I describe a range of linguistic resources that mark contrast and examine the semiotic relationships at play in the dynamic, multimodal signs (i.e. speech / gesture constructions) that accompany them. I demonstrate that, far from being ad hoc, when analyzed across the propositional, cognitive, and discursive domains, the way in which contrast is marked in the body can be viewed on a continuum of highly imageable to more schematically iconic kinesic movements. By placing the primary focus on the multimodal sign, this paper makes clear how speakers of North American English build semiotic environments around the construal of contrast.

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One of the most fundamental challenges when accessing gestural patterns in 3D motion capture databases is the definition of spatiotemporal similarity. While distance-based similarity models such as the Gesture Matching Distance on gesture signatures are able to leverage the spatial and temporal characteristics of gestural patterns, their applicability to large 3D motion capture databases is limited due to their high computational complexity. To this end, we present a lower bound approximation of the Gesture Matching Distance that can be utilized in an optimal multi-step query processing architecture in order to support efficient query processing. We investigate the performance in terms of accuracy and efficiency based on 3D motion capture databases and show that our approach is able to achieve an increase in efficiency of more than one order of magnitude with a negligible loss in accuracy. In addition, we discuss different applications in the digital humanities in order to highlight the significance of similarity search approaches in the research field of gestural pattern analysis.