A well-established finding in the simulation literature is that participants simulate the positive argument of negation soon after reading a negative sentence, prior to simulating a scene consistent with the negated sentence (Kaup, Ludtke, & Zwaan, 2006; Kaup, Yaxley, Madden, Zwaan, & Ludtke, 2007). One interpretation of this finding is that negation requires two steps to process: first represent what is being negated then "reject" that in favour of a representation of a negation-consistent state of affairs (Kaup et al., 2007). In this paper we argue that this finding with negative sentences could be a by-product of the dynamic way that language is interpreted relative to a common ground and not the way that negation is represented. We present a study based on Kaup et al. (2007) that tests the competing accounts. Our results suggest that some negative sentences are not processed in two steps, but provide support for the alternative, dynamic account.

When processing negative sentences without context, participants often represent states of the positive arguments. Why and when does this occur? Using visual world eyetracking, participants listened to positive and negative sentences in simple or cleft forms (e.g. [It is] Matt [who] hasn't shut his dad's window), while looking at scenes containing a target and a competitor (matches or mismatches the implied shape of the final noun). Results show that in the simple but not the cleft condition, there is a difference between negatives and positives: shortly after the verb, there is more looks to the competitor in the simple negatives than the positives. This suggests that the representation of the positive is not a mandatory first step of negation processing (as per rejection accounts). Rather results support the Question Under Discussion (QUD) accommodation account wherein both sentence content and contextual source of relevance are targets of incremental sentence processing.

L AUGHTER is a crucial signal for communication and managing interactions. Until now no consensual approach has emerged for classifying laughter. We propose a new framework for laughter analysis and classification, based on the pivotal assumption that laughter has propositional content. We propose an annotation scheme to classify the pragmatic functions of laughter taking into account the form, the laughable, the social, situational, and linguistic context. We apply the framework and taxonomy proposed in a multilingual corpus study (French, Mandarin Chinese and English), involving a variety of situational contexts. Our results give rise to novel generalizations about the range of meanings laughter exhibits, the placement of the laughable, and how placement and arousal relate to the functions of laughter. We have tested and refuted the validity of the commonly accepted assumption that laughter directly follows its laughable. In the concluding section, we discuss the implications our work has for spoken dialogue systems. We stress that laughter integration in spoken dialogue systems is not only crucial for emotional and affective computing aspects, but also for aspects related to natural language understanding and pragmatic reasoning. We formulate the emergent computational challenges for incorporating laughter in spoken dialogue systems.

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