4 resultados para Catalan language -- Words, New

em National Center for Biotechnology Information - NCBI


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At the forefront of debates on language are new data demonstrating infants' early acquisition of information about their native language. The data show that infants perceptually “map” critical aspects of ambient language in the first year of life before they can speak. Statistical properties of speech are picked up through exposure to ambient language. Moreover, linguistic experience alters infants' perception of speech, warping perception in the service of language. Infants' strategies are unexpected and unpredicted by historical views. A new theoretical position has emerged, and six postulates of this position are described.

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To investigate the types of memory traces recovered by the medial temporal lobe (MTL), neural activity during veridical and illusory recognition was measured with the use of functional MRI (fMRI). Twelve healthy young adults watched a videotape segment in which two speakers alternatively presented lists of associated words, and then the subjects performed a recognition test including words presented in the study lists (True items), new words closely related to studied words (False items), and new unrelated words (New items). The main finding was a dissociation between two MTL regions: whereas the hippocampus was similarly activated for True and False items, suggesting the recovery of semantic information, the parahippocampal gyrus was more activated for True than for False items, suggesting the recovery of perceptual information. The study also yielded a dissociation between two prefrontal cortex (PFC) regions: whereas bilateral dorsolateral PFC was more activated for True and False items than for New items, possibly reflecting monitoring of retrieved information, left ventrolateral PFC was more activated for New than for True and False items, possibly reflecting semantic processing. Precuneus and lateral parietal regions were more activated for True and False than for New items. Orbitofrontal cortex and cerebellar regions were more activated for False than for True items. In conclusion, the results suggest that activity in anterior MTL regions does not distinguish True from False, whereas activity in posterior MTL regions does.

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This article reviews attempts to characterize the mental operations mediated by left inferior prefrontal cortex, especially the anterior and inferior portion of the gyrus, with the functional neuroimaging techniques of positron emission tomography and functional magnetic resonance imaging. Activations in this region occur during semantic, relative to nonsemantic, tasks for the generation of words to semantic cues or the classification of words or pictures into semantic categories. This activation appears in the right prefrontal cortex of people known to be atypically right-hemisphere dominant for language. In this region, activations are associated with meaningful encoding that leads to superior explicit memory for stimuli and deactivations with implicit semantic memory (repetition priming) for words and pictures. New findings are reported showing that patients with global amnesia show deactivations in the same region associated with repetition priming, that activation in this region reflects selection of a response from among numerous relative to few alternatives, and that activations in a portion of this region are associated specifically with semantic relative to phonological processing. It is hypothesized that activations in left inferior prefrontal cortex reflect a domain-specific semantic working memory capacity that is invoked more for semantic than nonsemantic analyses regardless of stimulus modality, more for initial than for repeated semantic analysis of a word or picture, more when a response must be selected from among many than few legitimate alternatives, and that yields superior later explicit memory for experiences.

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The field of natural language processing (NLP) has seen a dramatic shift in both research direction and methodology in the past several years. In the past, most work in computational linguistics tended to focus on purely symbolic methods. Recently, more and more work is shifting toward hybrid methods that combine new empirical corpus-based methods, including the use of probabilistic and information-theoretic techniques, with traditional symbolic methods. This work is made possible by the recent availability of linguistic databases that add rich linguistic annotation to corpora of natural language text. Already, these methods have led to a dramatic improvement in the performance of a variety of NLP systems with similar improvement likely in the coming years. This paper focuses on these trends, surveying in particular three areas of recent progress: part-of-speech tagging, stochastic parsing, and lexical semantics.