54 resultados para Corpus-Based Translation Studies

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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Objective: To examine the potential biases arising from the nonlinkage of census records and vital events in longitudinal studies.
Study Design and Setting: A total of 56,396 deaths of residents of Northern Ireland in the 4 years after the 2001 Census were linked to the 2001 Census records. The characteristics of matched and nonmatched death records were compared using multivariate logistic regression. Subject attributes were as recorded on the death certificate.
Results: In total, 3,392 (6.0%) deaths could not be linked to a census record. Linkage rates were lowest in young adults, males, the unmarried, people living in communal establishments, or living in areas that were more deprived or had recorded low census enumeration. For those aged less than 65 years at census, this linkage would exclude from analysis 20.2% of suicides and 19.7% of deaths by external causes.
Conclusion: The nonlinkage of census and death records is a combination of nonenumeration at census and deficient information about the deceased recorded at the time of death. Unmatched individuals may have been more disadvantaged or socially isolated, and analysis based on the linked data set may therefore show some bias and perhaps understate true social gradients.

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This article explores the historical neglect of translation as a consideration in the study and practice of theatre in the United States and Europe. While the study of literature is fairly strictly divided between English-language and Comparative Literature departments, theatre and drama have shown little concern about language as a barrier to reception of the dramatic text. Arguably, this discrepancy may be traced to a fundamental gap between the perceived status of the novel as a completed work of art and the playtext as work of art in progress, waiting to find its completion in performance.

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Dysfunction of lipid-metabolizing proteins is implicated in the pathogenesis of coronary artery disease. Single nucleotide polymorphisms in genes that encode sterol regulatory binding protein-la, adenosine triphosphate binding cassette-A1, hepatic lipase, lipoprotein lipase, and cholesteryl ester transfer protein were assessed as potential markers of disease susceptibility in a family-based study of 1,012 patients from 386 families. Association between single nucleotide polymorphisms and coronary artery disease was tested by the combined transmission disequilibrium test/sib transmission disequilibrium test and pedigree disequilibrium test. After Bonferroni's correction, the pedigree disequilibrium test demonstrated significant excess transmission (p < 0.0083) to affected patients of the hepatic lipase -514 T allele, which suggests that this may constitute a novel disease-susceptibility locus. (c) 2005 Elsevier Inc. All rights reserved.

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Starting from the premise that human communication is predicated on translational phenomena, this paper applies theoretical insights and practical findings from Translation Studies to a critique of Natural Semantic Metalanguage (NSM), a theory of semantic analysis developed by Anna Wierzbicka. Key tenets of NSM, i.e. (1) culture-specificity of complex concepts; (2) the existence of a small set of universal semantic primes; and (3) definition by reductive paraphrase, are discussed critically with reference to the notions of untranslatability, equivalence, and intra-lingual translation, respectively. It is argued that a broad spectrum of research and theoretical reflection in Translation Studies may successfully feed into the study of cognition, meaning, language, and communication. The interdisciplinary exchange between Translation Studies and linguistics may be properly balanced, with the former not only being informed by but also informing and interrogating the latter.

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Temporal dynamics and speaker characteristics are two important features of speech that distinguish speech from noise. In this paper, we propose a method to maximally extract these two features of speech for speech enhancement. We demonstrate that this can reduce the requirement for prior information about the noise, which can be difficult to estimate for fast-varying noise. Given noisy speech, the new approach estimates clean speech by recognizing long segments of the clean speech as whole units. In the recognition, clean speech sentences, taken from a speech corpus, are used as examples. Matching segments are identified between the noisy sentence and the corpus sentences. The estimate is formed by using the longest matching segments found in the corpus sentences. Longer speech segments as whole units contain more distinct dynamics and richer speaker characteristics, and can be identified more accurately from noise than shorter speech segments. Therefore, estimation based on the longest recognized segments increases the noise immunity and hence the estimation accuracy. The new approach consists of a statistical model to represent up to sentence-long temporal dynamics in the corpus speech, and an algorithm to identify the longest matching segments between the noisy sentence and the corpus sentences. The algorithm is made more robust to noise uncertainty by introducing missing-feature based noise compensation into the corpus sentences. Experiments have been conducted on the TIMIT database for speech enhancement from various types of nonstationary noise including song, music, and crosstalk speech. The new approach has shown improved performance over conventional enhancement algorithms in both objective and subjective evaluations.

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Computational models of meaning trained on naturally occurring text successfully model human performance on tasks involving simple similarity measures, but they characterize meaning in terms of undifferentiated bags of words or topical dimensions. This has led some to question their psychological plausibility (Murphy, 2002; Schunn, 1999). We present here a fully automatic method for extracting a structured and comprehensive set of concept descriptions directly from an English part-of-speech-tagged corpus. Concepts are characterized by weighted properties, enriched with concept-property types that approximate classical relations such as hypernymy and function. Our model outperforms comparable algorithms in cognitive tasks pertaining not only to concept-internal structures (discovering properties of concepts, grouping properties by property type) but also to inter-concept relations (clustering into superordinates), suggesting the empirical validity of the property-based approach. Copyright © 2009 Cognitive Science Society, Inc. All rights reserved.

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Background: The aim was to collate all myasthenia gravis (MG) epidemiological studies including AChR MG and MuSK MG specific studies. To synthesize data on incidence rate (IR), prevalence rate (PR) and mortality rate (MR) of the condition and investigate the influence of environmental and technical factors on any trends or variation observed.

Methods: Studies were identified using multiple sources and meta-analysis performed to calculate pooled estimates for IR, PR and MR.

Results: 55 studies performed between 1950 and 2007 were included, representing 1.7 billion population-years. For All MG estimated pooled IR (eIR): 5.3 per million person-years (C.I.: 4.4, 6.1), range: 1.7 to 21.3; estimated pooled PR: 77.7 per illion persons (C.I.: 64.0, 94.3), range 15 to 179; MR range 0.1 to 0.9 per millions person-years. AChR MG eIR: 7.3 (C.I.: 5.5, 7.8), range: 4.3 to 18.0; MuSK MG IR range: 0.1 to 0.32. However marked variation persisted between populations studied with similar methodology and in similar areas.

Conclusions: We report marked variation in observed frequencies of MG. We show evidence of increasing frequency of MG with year of study and improved study quality. This probably reflects improved case ascertainment. But other factors must also influence disease onset resulting in the observed variation in IR across geographically and genetically similar populations.

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This paper presents a new approach to single-channel speech enhancement involving both noise and channel distortion (i.e., convolutional noise). The approach is based on finding longest matching segments (LMS) from a corpus of clean, wideband speech. The approach adds three novel developments to our previous LMS research. First, we address the problem of channel distortion as well as additive noise. Second, we present an improved method for modeling noise. Third, we present an iterative algorithm for improved speech estimates. In experiments using speech recognition as a test with the Aurora 4 database, the use of our enhancement approach as a preprocessor for feature extraction significantly improved the performance of a baseline recognition system. In another comparison against conventional enhancement algorithms, both the PESQ and the segmental SNR ratings of the LMS algorithm were superior to the other methods for noisy speech enhancement. Index Terms: corpus-based speech model, longest matching segment, speech enhancement, speech recognition

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Background: Underweight and severe and morbid obesity are associated with highly elevated risks of adverse health outcomes. We estimated trends in mean body-mass index (BMI), which characterises its population distribution, and in the prevalences of a complete set of BMI categories for adults in all countries.

Methods: We analysed, with use of a consistent protocol, population-based studies that had measured height and weight in adults aged 18 years and older. We applied a Bayesian hierarchical model to these data to estimate trends from 1975 to 2014 in mean BMI and in the prevalences of BMI categories (<18·5 kg/m2 [underweight], 18·5 kg/m2 to <20 kg/m2, 20 kg/m2 to <25 kg/m2, 25 kg/m2 to <30 kg/m2, 30 kg/m2 to <35 kg/m2, 35 kg/m2 to <40 kg/m2, ≥40 kg/m2 [morbid obesity]), by sex in 200 countries and territories, organised in 21 regions. We calculated the posterior probability of meeting the target of halting by 2025 the rise in obesity at its 2010 levels, if post-2000 trends continue.
Findings: We used 1698 population-based data sources, with more than 19·2 million adult participants (9·9 million men and 9·3 million women) in 186 of 200 countries for which estimates were made. Global age-standardised mean BMI increased from 21·7 kg/m2 (95% credible interval 21·3–22·1) in 1975 to 24·2 kg/m2 (24·0–24·4) in 2014 in men, and from 22·1 kg/m2 (21·7–22·5) in 1975 to 24·4 kg/m2 (24·2–24·6) in 2014 in women. Regional mean BMIs in 2014 for men ranged from 21·4 kg/m2 in central Africa and south Asia to 29·2 kg/m2 (28·6–29·8) in Polynesia and Micronesia; for women the range was from 21·8 kg/m2 (21·4–22·3) in south Asia to 32·2 kg/m2 (31·5–32·8) in Polynesia and Micronesia. Over these four decades, age-standardised global prevalence of underweight decreased from 13·8% (10·5–17·4) to 8·8% (7·4–10·3) in men and from 14·6% (11·6–17·9) to 9·7% (8·3–11·1) in women. South Asia had the highest prevalence of underweight in 2014, 23·4% (17·8–29·2) in men and 24·0% (18·9–29·3) in women. Age-standardised prevalence of obesity increased from 3·2% (2·4–4·1) in 1975 to 10·8% (9·7–12·0) in 2014 in men, and from 6·4% (5·1–7·8) to 14·9% (13·6–16·1) in women. 2·3% (2·0–2·7) of the world's men and 5·0% (4·4–5·6) of women were severely obese (ie, have BMI ≥35 kg/m2). Globally, prevalence of morbid obesity was 0·64% (0·46–0·86) in men and 1·6% (1·3–1·9) in women.

Interpretation: If post-2000 trends continue, the probability of meeting the global obesity target is virtually zero. Rather, if these trends continue, by 2025, global obesity prevalence will reach 18% in men and surpass 21% in women; severe obesity will surpass 6% in men and 9% in women. Nonetheless, underweight remains prevalent in the world's poorest regions, especially in south Asia.