Computational and animal models suggest that the unlearning or pruning of incorrect meanings matters for word learning. However, it is currently unclear how such pruning occurs during word learning and to what extent it depends on supervised and unsupervised learning. In two experiments (N[subscript 1] = 40; N[subscript 2] = 42), adult…

Distributional models of semantics learn word meanings from contextual co-occurrence patterns across a large sample of natural language. Early models, such as LSA and HAL (Landauer & Dumais, 1997; Lund & Burgess, 1996), counted co-occurrence events; later models, such as BEAGLE (Jones & Mewhort, 2007), replaced counting co-occurrences…

Productivity is a central concept in the study of language and language acquisition. As a test case for exploring the notion of productivity, we focus on the noun slots of verb frames, such as __"want"__, __"see"__, and __"get"__. We develop a novel combination of measures designed to assess both the flexibility and…

Despite the fact that they play a prominent role in everyday speech, the representation and processing of fixed expressions during language production is poorly understood. Here, we report a study investigating the processes underlying fixed expression production. "Tip-of-the-tongue" (TOT) states were elicited for well-known idioms…