Three experiments investigated the processing of the implicature associated with some using a “gumball paradigm.” On each trial, participants saw an image of a gumball machine with an upper chamber with 13 gumballs and an empty lower chamber. Gumballs then dropped to the lower chamber and participants evaluated statements, such as “You got some of the gumballs.” Experiment 1 established that some is less natural for reference to small sets and unpartitioned sets compared to intermediate sets. Partitive some of was (...) less natural than simple some when used with the unpartitioned set. In Experiment 2, including exact number descriptions lowered naturalness ratings for some with small sets but not for intermediate size sets and the unpartitioned set. In Experiment 3, the naturalness ratings from Experiment 2 predicted response times. The results are interpreted as evidence for a Constraint-Based account of scalar implicature processing and against both two-stage, Literal-First models and pragmatic Default models. (shrink)
The notion of common ground is important for the production of referring expressions: In order for a referring expression to be felicitous, it has to be based on shared information. But determining what information is shared and what information is privileged may require gathering information from multiple sources, and constantly coordinating and updating them, which might be computationally too intensive to affect the earliest moments of production. Previous work has found that speakers produce overinformative referring expressions, which include privileged names, (...) violating Grice’s Maxims, and concluded that this is because they do not mark the distinction between shared and privileged information. We demonstrate that speakers are in fact quite effective in marking this distinction in the form of their utterances. Nonetheless, under certain circumstances, speakers choose to overspecify privileged names. (shrink)
Two visual world experiments investigated the processing of the implicature associated with some using a “gumball paradigm.” On each trial, participants saw an image of a gumball machine with an upper chamber with orange and blue gumballs and an empty lower chamber. Gumballs dropped to the lower chamber, creating a contrast between a partitioned set of gumballs of one color and an unpartitioned set of the other. Participants then evaluated spoken statements, such as “You got some of the blue gumballs.” (...) Experiment 1 investigated the time course of the pragmatic enrichment from some to not all when the only utterance alternatives available to refer to the different sets were some and all. In Experiment 2, the number terms two, three, four, and five were also included in the set of alternatives. Scalar implicatures were delayed relative to the interpretation of literal statements with all only when number terms were available. The results are interpreted as evidence for a constraint-based account of scalar implicature processing. (shrink)
We propose, following Clark, that generative models also play a central role in the perception and interpretation of linguistic signals. The data explanation approach provides a rationale for the role of prediction in language processing and unifies a number of phenomena, including multiple-cue integration, adaptation effects, and cortical responses to violations of linguistic expectations.
Since Horn (1972) the notion of conversational implicature proposed by Grice has been put to use to explain certain interpretive differences between expressions in natural language and their counterparts in formal logic. For example, the sentences in (1) seem to convey more than they would be expected to if the natural language disjunction or had the same meaning as the logical disjunction ∨, or if the quantiﬁcational determiner some was interpreted as the existential quantiﬁer ∃.
Christiansen & Chater propose that language comprehenders must immediately compress perceptual data by “chunking” them into higher-level categories. Effective language understanding, however, requires maintaining perceptual information long enough to integrate it with downstream cues. Indeed, recent results suggest comprehenders do this. Although cognitive systems are undoubtedly limited, frameworks that do not take into account the tasks that these systems evolved to solve risk missing important insights.
We agree with Pickering & Garrod's (P&G's) proposal that dialogue is an important empirical and theoretical test bed for models of language processing. However, we offer two cautionary notes. First, the enterprise will require explicit computational models. Second, such models will need to incorporate both joint and separate speaker and hearer commitments in ways that go beyond priming and alignment.