940 resultados para NLP (Natural Language Processing)


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Las bases de datos geoespaciales temáticas en distintas escalas geográficas y temporales, son necesarias en multitud de líneas de investigación. Una de ellas es la gestión y alerta temprana de riesgos de desastres por amenazas naturales (inundaciones, huracanes, terremotos, etc.). Las noticias sobre éste tema se publican habitualmente en periódicos digitales de todo el mundo y comportan un alto contenido geográfico. Este trabajo pretende extraer automáticamente las noticias emitidas por canales de re-difusión web (conocidos por las siglas RSS en inglés) para georreferenciarlas, almacenarlas y distribuirlas como datos geoespaciales. Mediante técnicas de procesamiento de lenguaje natural y consultas a bases de datos de topónimos realizaremos la extracción de la información. El caso de estudio se aplicará para México y todos los componentes utilizados serán de código abierto

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A presente pesquisa tem como Questão Central a avaliação da estrutura da narrativa por um grupo de seis crianças surdas profundas utilizando a Língua Gestual Portuguesa (LGP). Neste estudo questionou-se se se encontrariam diferenças na produção da narrativa entre crianças que adquiriram a LGP precocemente e as que tiveram o primeiro contato com a língua materna tardiamente. Colocou-se a hipótese geral que a língua natural das crianças surdas portuguesas é a LGP e as que tiveram um acesso precoce à sua língua apresentam um melhor desempenho na narração de uma história. Para verificar esta hipótese, foi aplicada uma prova que consistia no conto de uma história, a partir de uma sequência de imagens, em LGP a todos as crianças desta investigação. Releva-se a importância de um precoce ambiente comunicativo para que a criança surda adquira um desenvolvimento global semelhante aos seus pares ouvintes. Salienta-se ainda que a influência dos pais, dos educadores e dos professores é fundamental para que a criança surda possa desenvolver a sua língua natural, a LGP e a aprendizagem da segunda língua. Os resultados obtidos confirmaram as hipóteses colocadas, ou seja, as crianças que adquiriram precocemente a LGP apresentaram um maior desenvolvimento na estrutura da narrativa.

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A língua gestual (LG) é a língua natural da pessoa surda, sendo utilizada como forma de expressão e comunicação da comunidade surda de um determinado país. Porém, é de todo impossível escrever estas línguas através de um alfabeto comum como o da Língua Portuguesa (LP). Em 1974, na Dinamarca, Valerie Sutton criou o SignWriting (SW), um sistema de escrita das línguas gestuais, contrariando assim a ideia de que as línguas espaço-visuais não poderiam ter uma representação gráfica. Para o surgimento deste sistema foram fundamentais os estudos pioneiros de William Stokoe que reconheceram o estatuto linguístico das línguas gestuais, atribuindo-lhes propriedades inerentes a uma língua, como por exemplo a arbitrariedade e convencionalidade. Neste trabalho apresentamos o SW, sistema de escrita das línguas gestuais já utilizado noutros países, e questionamos se é exequível e profícua a sua adaptação à língua gestual portuguesa (LGP). Nesse sentido, concretizamos a escrita da LGP com base em áreas vocabulares distintas e presentes no programa curricular do ensino da LGP. Por último, efetivamos tal proposta através de um modelo de ação de formação em SW.

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We present the symbolic resonance analysis (SRA) as a viable method for addressing the problem of enhancing a weakly dominant mode in a mixture of impulse responses obtained from a nonlinear dynamical system. We demonstrate this using results from a numerical simulation with Duffing oscillators in different domains of their parameter space, and by analyzing event-related brain potentials (ERPs) from a language processing experiment in German as a representative application. In this paradigm, the averaged ERPs exhibit an N400 followed by a sentence final negativity. Contemporary sentence processing models predict a late positivity (P600) as well. We show that the SRA is able to unveil the P600 evoked by the critical stimuli as a weakly dominant mode from the covering sentence final negativity. (c) 2007 American Institute of Physics. (c) 2007 American Institute of Physics.

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Background: As people age, language-processing ability changes. While several factors modify discourse comprehension ability in older adults, syntactic complexity of auditory discourse has received scant attention. This is despite the widely researched domain of syntactic processing of single sentences in older adults. Aims: The aims of this study were to investigate the ability of healthy older adults to understand stories that differed in syntactic complexity, and its relation to working memory. Methods & Procedures: A total of 51 healthy adults (divided into three age groups) took part. They listened to brief stories (syntactically simple and syntactically complex) and had to respond to false/true comprehension probes following each story. Working memory capacity (digit span, forward and backward) was also measured. Outcomes & Results: Differences were found in the ability of healthy older adults to understand simple and complex discourse. The complex discourse in particular was more sensitive in discerning age-related language patterns. Only the complex discourse task correlated moderately with age. There was no correlation between age and simple discourse. As far as working memory is concerned, moderate correlations were found between working memory and complex discourse. Education did not correlate with discourse, neither simple, nor complex. Conclusions: Older adults may be less efficient in forming syntactically complex representations and this may be influenced by limitations in working memory.

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Chatterbox Challenge is an annual web-based contest for artificial conversational systems, ACE. The 2010 instantiation was the tenth consecutive contest held between March and June in the 60th year following the publication of Alan Turing’s influential disquisition ‘computing machinery and intelligence’. Loosely based on Turing’s viva voca interrogator-hidden witness imitation game, a thought experiment to ascertain a machine’s capacity to respond satisfactorily to unrestricted questions, the contest provides a platform for technology comparison and evaluation. This paper provides an insight into emotion content in the entries since the 2005 Chatterbox Challenge. The authors find that synthetic textual systems, none of which are backed by academic or industry funding, are, on the whole and more than half a century since Weizenbaum’s natural language understanding experiment, little further than Eliza in terms of expressing emotion in dialogue. This may be a failure on the part of the academic AI community for ignoring the Turing test as an engineering challenge.

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Purpose – The purpose of this paper is to consider Turing's two tests for machine intelligence: the parallel-paired, three-participants game presented in his 1950 paper, and the “jury-service” one-to-one measure described two years later in a radio broadcast. Both versions were instantiated in practical Turing tests during the 18th Loebner Prize for artificial intelligence hosted at the University of Reading, UK, in October 2008. This involved jury-service tests in the preliminary phase and parallel-paired in the final phase. Design/methodology/approach – Almost 100 test results from the final have been evaluated and this paper reports some intriguing nuances which arose as a result of the unique contest. Findings – In the 2008 competition, Turing's 30 per cent pass rate is not achieved by any machine in the parallel-paired tests but Turing's modified prediction: “at least in a hundred years time” is remembered. Originality/value – The paper presents actual responses from “modern Elizas” to human interrogators during contest dialogues that show considerable improvement in artificial conversational entities (ACE). Unlike their ancestor – Weizenbaum's natural language understanding system – ACE are now able to recall, share information and disclose personal interests.

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This study investigates the two later-acquired but proficient languages, English and Hindi, of two multilingual individuals with transcortical aphasia (right basal ganglia lesion in GN and brain stem lesion in GS). Dissociation between lexical and syntactic profiles in both the languages with a uniform performance across the languages at the lexical level and an uneven performance across the languages at the syntactic level was observed. Their performances are discussed in relation to the implicit/explicit language processes (Paradis, 1994 and Paradis, 2004) and the declarative/procedural model (Ullman, 2001b and Ullman, 2005) of bilingual language processing. Additionally, their syntactic performance is interpreted in relation to the salient grammatical contrasts between English and Hindi.

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The avoidance of regular but not irregular plurals inside compounds (e.g. *rats eater vs. mice eater) has been one of the most widely studied morphological phenomena in the psycholinguistics literature. To examine whether the constraints that are responsible for this contrast have any general significance beyond compounding, we investigated derived word forms containing regular and irregular plurals in two experiments. Experiment 1 was an offline acceptability judgment task, and experiment 2 measured eye movements during reading derived words containing regular and irregular plurals and uninflected base nouns. The results from both experiments show that the constraint against regular plurals inside compounds generalizes to derived words. We argue that this constraint cannot be reduced to phonological properties, but is instead morphological in nature. The eye-movement data provide detailed information on the time-course of processing derived word forms indicating that early stages of processing are affected by a general constraint that disallows inflected words from feeding derivational processes, and that the more specific constraint against regular plurals comes in at a subsequent later stage of processing. We argue that these results are consistent with stage-based models of language processing.

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Recent studies suggest that learning and using a second language (L2) can affect brain structure, including the structure of white matter (WM) tracts. This observation comes from research looking at early and older bilingual individuals who have been using both their first and second languages on an everyday basis for many years. This study investigated whether young, highly immersed late bilinguals would also show structural effects in the WM that can be attributed to everyday L2 use, irrespective of critical periods or the length of L2 learning. Our Tract-Based Spatial Statistics analysis revealed higher fractional anisotropy values for bilinguals vs. monolinguals in several WM tracts that have been linked to language processing and in a pattern closely resembling the results reported for older and early bilinguals. We propose that learning and actively using an L2 after childhood can have rapid dynamic effects on WM structure, which in turn may assist in preserving WM integrity in older age.

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Background: The validity of ensemble averaging on event-related potential (ERP) data has been questioned, due to its assumption that the ERP is identical across trials. Thus, there is a need for preliminary testing for cluster structure in the data. New method: We propose a complete pipeline for the cluster analysis of ERP data. To increase the signalto-noise (SNR) ratio of the raw single-trials, we used a denoising method based on Empirical Mode Decomposition (EMD). Next, we used a bootstrap-based method to determine the number of clusters, through a measure called the Stability Index (SI). We then used a clustering algorithm based on a Genetic Algorithm (GA)to define initial cluster centroids for subsequent k-means clustering. Finally, we visualised the clustering results through a scheme based on Principal Component Analysis (PCA). Results: After validating the pipeline on simulated data, we tested it on data from two experiments – a P300 speller paradigm on a single subject and a language processing study on 25 subjects. Results revealed evidence for the existence of 6 clusters in one experimental condition from the language processing study. Further, a two-way chi-square test revealed an influence of subject on cluster membership.

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Compared to skilled adult readers, children typically make more fixations that are longer in duration, shorter saccades, and more regressions, thus reading more slowly (Blythe & Joseph, 2011). Recent attempts to understand the reasons for these differences have discovered some similarities (e.g., children and adults target their saccades similarly; Joseph, Liversedge, Blythe, White, & Rayner, 2009) and some differences (e.g., children’s fixation durations are more affected by lexical variables; Blythe, Liversedge, Joseph, White, & Rayner, 2009) that have yet to be explained. In this article, the E-Z Reader model of eye-movement control in reading (Reichle, 2011; Reichle, Pollatsek, Fisher, & Rayner, 1998) is used to simulate various eye-movement phenomena in adults versus children in order to evaluate hypotheses about the concurrent development of reading skill and eye-movement behavior. These simulations suggest that the primary difference between children and adults is their rate of lexical processing, and that different rates of (post-lexical) language processing may also contribute to some phenomena (e.g., children’s slower detection of semantic anomalies; Joseph et al., 2008). The theoretical implications of this hypothesis are discussed, including possible alternative accounts of these developmental changes, how reading skill and eye movements change across the entire lifespan (e.g., college-aged vs. elderly readers), and individual differences in reading ability.

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This paper is about the use of natural language to communicate with computers. Most researches that have pursued this goal consider only requests expressed in English. A way to facilitate the use of several languages in natural language systems is by using an interlingua. An interlingua is an intermediary representation for natural language information that can be processed by machines. We propose to convert natural language requests into an interlingua [universal networking language (UNL)] and to execute these requests using software components. In order to achieve this goal, we propose OntoMap, an ontology-based architecture to perform the semantic mapping between UNL sentences and software components. OntoMap also performs component search and retrieval based on semantic information formalized in ontologies and rules.

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Using a new proposal for the ""picture lowering"" operators, we compute the tree level scattering amplitude in the minimal pure spinor formalism by performing the integration over the pure spinor space as a multidimensional Cauchy-type integral. The amplitude will be written in terms of the projective pure spinor variables, which turns out to be useful to relate rigorously the minimal and non-minimal versions of the pure spinor formalism. The natural language for relating these formalisms is the. Cech-Dolbeault isomorphism. Moreover, the Dolbeault cocycle corresponding to the tree-level scattering amplitude must be evaluated in SO(10)/SU(5) instead of the whole pure spinor space, which means that the origin is removed from this space. Also, the. Cech-Dolbeault language plays a key role for proving the invariance of the scattering amplitude under BRST, Lorentz and supersymmetry transformations, as well as the decoupling of unphysical states. We also relate the Green`s function for the massless scalar field in ten dimensions to the tree-level scattering amplitude and comment about the scattering amplitude at higher orders. In contrast with the traditional picture lowering operators, with our new proposal the tree level scattering amplitude is independent of the constant spinors introduced to define them and the BRST exact terms decouple without integrating over these constant spinors.