Hybrid models of speech comprehension assume two types of lexical representations for the pronunciation of words: abstract representations and exemplars (e.g., Goldinger, 2007; Hawkins, 2003). Abstract representations are strings of sounds symbols that do not contain details about words' exact pronunciations. Exemplars, in contrast, are highly detailed representations of word occurrences, which...

We investigated how another person's emotions about resource allocation decisions influence observers' resource allocations by influencing the emotions that observers anticipate feeling if they were to act in the same way. Participants were exposed to an exemplar who made a fair or unfair division in an economic game and expressed pride or regret about this decision. Participants then made thei...

We describe the performance of a Spectral Element Atmospheric Model (SEAM) on the HP Exemplar SPP2000. SEAM uses spectral elements in the horizontal directions and sigma coordinates in the vertical. The model is both spectrally accurate, as demonstrated by a variety of test cases, and is well suited for modern distributed-shared memory computers, as demonstrated by the fact that we achieve 24 G...

Children’s spatial language abilities relate to their spatial skills. We propose that this relation arises from attention to spatial dimensions influencing both spatial word and spatial skill acquisition. This study tests whether attending to spatial dimensions in a word learning task predicts spatial vocabulary. Three to 5-year-olds completed a novel word assessment testing categorization of a...

Three experiments tested the exemplar cuing and frequency format accounts of how the ‘imaginability’ of low-probability events is enhanced. The experiments manipulated imaginability by varying the statistics used to describe negative (e.g. being scarred as a result of laser surgery) and positive (e.g. winning a lottery) low-probability events. The results strongly supported the frequency format...

Exemplar-based methods have proven their efficiency for the reconstruction of missing parts in a digital image. Texture as well as local geometry are often very well restored by these methods. Some applications, however, require the ability to reconstruct non local geometric features, e.g. long edges. We propose in this paper to endow a particular instance of exemplar-based method with a geomet...

This paper describes a novel exemplar-based spectral conversion (SC) system developed by the AST (Academia Sinica, Taipei) team for the 2016 voice conversion challenge (vcc2016). The key feature of our system is that it integrates the locally linear embedding (LLE) algorithm, a manifold learning algorithm that has been successfully applied for the super-resolution task in image processing, with...

Learning in imbalanced domains is one of the recent challenges in machine learning and data mining. In imbalanced classification, data sets present many examples from one class and few from the other class, and the latter class is the one which receives more interest from the point of view of learning. One of the most used techniques to deal with this problem consists in preprocessing the data ...

Making accurate judgments is an essential skill in everyday life. Although how different memory abilities relate to categorization and judgment processes has been hotly debated, the question is far from resolved. We contribute to the solution by investigating how individual differences in memory abilities affect judgment performance in 2 tasks that induced rule-based or exemplar-based judgment ...

This paper introduces a novel approach to in-painting where the identity of the object to remove or change is preserved and accounted for at inference time: Exemplar GANs (ExGANs). ExGANs are a type of conditional GAN that utilize exemplar information to produce high-quality, personalized in-painting results. We propose using exemplar information in the form of a reference image of the region t...