OBJECTIVES In two experiments with different subject groups, we explored the relationship between semantic context and intelligibility by examining the influence of visually presented, semantically related, and unrelated three-word text cues on perception of spoken sentences in stationary noise across a range of speech-to-noise ratios (SNRs). In addition, in Experiment (Exp) 2, we explored the ...

In word retrieval, speakers need to select a lexical entry among several co-activated candidates for lexicalization. How a target entry is selected is a matter of ongoing debate. Semantic context effects on naming times, as seen in the blocked-cyclic naming paradigm, are of specific interest to this debate. In the standard version of this paradigm, participants name lists of objects compiled fr...

We consider the task of learning visual connections between object categories using the ImageNet dataset, which is a large-scale dataset ontology containing more than 15 thousand object classes. We want to discover visual relationships between the classes that are currently missing (such as similar colors or shapes or textures). In this work we learn 20 visual attributes and use them in a zero-...

Two experiments are reported in which naming multidigit Arabic numerals was shown to depend on the context in which the numbers were presented. Number naming and number decisions were faster after an associative prime (e.g., 747 preceded by the word Boeing) than after an unrelated prime, both in unmasked and masked priming conditions. On the basis of these findings, we conclude that number nami...

Numerous studies have examined sleep's influence on a range of hippocampus-dependent declarative memory tasks, from text learning to spatial navigation. In this study, we examined the impact of sleep, wake, and time-of-day influences on the processing of declarative information with strong semantic links (semantically related word pairs) and information requiring the formation of novel associat...

We present an adversarial framework to craft perturbations that mislead classifiers by accounting for the image content and semantics of labels. The proposed combines a structure loss semantic in multi-task objective function train fully convolutional neural network. helps generate whose type magnitude are defined target processing filter. considers groups (semantic) labels prevent filtered {fr...

Introduction Lexico-semantic disturbances are considered central to schizophrenia. Clinically, their clearest manifestation is in language production. However, most studies probing their underlying mechanisms have used comprehension or categorization tasks. Here, we probed automatic semantic activity prior to language production in schizophrenia using event-related potentials (ERPs). Methods ...

Three target words (T1, T2, and T3) were embedded in a rapid serial visual presentation (RSVP) stream of non-word distractors, and participants were required to report the targets at the end of each RSVP stream. T2 and T3 were semantically related words in half of the RSVP streams, and semantically unrelated words in the other half of the RSVP streams. Using an identical design, a recent study ...

Children’s ability to name an object by multiple semantically similar labels (i.e. synonyms) has been documented by the age of three; however, the ability to reason using semantically similar labels remains sparsely investigated. The present study expands our understanding of children’s ability to utilize semantically similar labels in two relational reasoning tasks – a semantic completion task...