58 resultados para automatic translation
Resumo:
The work presented here is part of a larger study to identify novel technologies and biomarkers for early Alzheimer disease (AD) detection and it focuses on evaluating the suitability of a new approach for early AD diagnosis by non-invasive methods. The purpose is to examine in a pilot study the potential of applying intelligent algorithms to speech features obtained from suspected patients in order to contribute to the improvement of diagnosis of AD and its degree of severity. In this sense, Artificial Neural Networks (ANN) have been used for the automatic classification of the two classes (AD and control subjects). Two human issues have been analyzed for feature selection: Spontaneous Speech and Emotional Response. Not only linear features but also non-linear ones, such as Fractal Dimension, have been explored. The approach is non invasive, low cost and without any side effects. Obtained experimental results were very satisfactory and promising for early diagnosis and classification of AD patients.
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Alzheimer's disease is the most prevalent form of progressive degenerative dementia; it has a high socio-economic impact in Western countries. Therefore it is one of the most active research areas today. Alzheimer's is sometimes diagnosed by excluding other dementias, and definitive confirmation is only obtained through a post-mortem study of the brain tissue of the patient. The work presented here is part of a larger study that aims to identify novel technologies and biomarkers for early Alzheimer's disease detection, and it focuses on evaluating the suitability of a new approach for early diagnosis of Alzheimer’s disease by non-invasive methods. The purpose is to examine, in a pilot study, the potential of applying Machine Learning algorithms to speech features obtained from suspected Alzheimer sufferers in order help diagnose this disease and determine its degree of severity. Two human capabilities relevant in communication have been analyzed for feature selection: Spontaneous Speech and Emotional Response. The experimental results obtained were very satisfactory and promising for the early diagnosis and classification of Alzheimer’s disease patients.
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In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used, and Principal Component Analysis (PCA) is applied in order to study which is the best number of components for the classification task, implemented by means of a Support Vector Machine (SVM) System. Obtained results are satisfactory, and compared with [4] our system improves the recognition success, diminishing the variance at the same time.
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In this work we present a simulation of a recognition process with perimeter characterization of a simple plant leaves as a unique discriminating parameter. Data coding allowing for independence of leaves size and orientation may penalize performance recognition for some varieties. Border description sequences are then used to characterize the leaves. Independent Component Analysis (ICA) is then applied in order to study which is the best number of components to be considered for the classification task, implemented by means of an Artificial Neural Network (ANN). Obtained results with ICA as a pre-processing tool are satisfactory, and compared with some references our system improves the recognition success up to 80.8% depending on the number of considered independent components.
Resumo:
Alzheimer’s disease (AD) is the most prevalent form of progressive degenerative dementia and it has a high socio-economic impact in Western countries, therefore is one of the most active research areas today. Its diagnosis is sometimes made by excluding other dementias, and definitive confirmation must be done trough a post-mortem study of the brain tissue of the patient. The purpose of this paper is to contribute to im-provement of early diagnosis of AD and its degree of severity, from an automatic analysis performed by non-invasive intelligent methods. The methods selected in this case are Automatic Spontaneous Speech Analysis (ASSA) and Emotional Temperature (ET), that have the great advantage of being non invasive, low cost and without any side effects.
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Although paraphrasing is the linguistic mechanism underlying many plagiarism cases, little attention has been paid to its analysis in the framework of automatic plagiarism detection. Therefore, state-of-the-art plagiarism detectors find it difficult to detect cases of paraphrase plagiarism. In this article, we analyse the relationship between paraphrasing and plagiarism, paying special attention to which paraphrase phenomena underlie acts of plagiarism and which of them are detected by plagiarism detection systems. With this aim in mind, we created the P4P corpus, a new resource which uses a paraphrase typology to annotate a subset of the PAN-PC-10 corpus for automatic plagiarism detection. The results of the Second International Competition on Plagiarism Detection were analysed in the light of this annotation. The presented experiments show that (i) more complex paraphrase phenomena and a high density of paraphrase mechanisms make plagiarism detection more difficult, (ii) lexical substitutions are the paraphrase mechanisms used the most when plagiarising, and (iii) paraphrase mechanisms tend to shorten the plagiarized text. For the first time, the paraphrase mechanisms behind plagiarism have been analysed, providing critical insights for the improvement of automatic plagiarism detection systems.
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In response to an increasing need for ever-shorter personality instruments, Gosling, Rentfrow, and Swann (2003) developed the Ten-Item-Personality Inventory (TIPI), which measures the dimensions of the Five Factor Model (FFM) using 10 items (two for each dimension) and can be administered in about one minute. In two studies and using a multi-judge (self and observer) and multi-instrument design, we develop Spanish (Castilian) and Catalan versions of the TIPI and evaluate them in terms of internal consistency, test-retest reliability, convergent, discriminant, and content validity, as well as self-observer correlations. Test-retest correlations were strong, and convergence with the NEO-PI-R factors was significant. There were also strong correlations between observer ratings and the participants’ self-ratings. Despite some inconsistencies with respect to the Agreeableness scale, the Catalan translation and both translations into Spanish of the original TIPI demonstrated sufficient psychometric properties to warrant use as a Five Factor personality measure when the use of longer instruments is not convenient or possible. Furthermore, as the first translation of a brief standard Big Five Instrument into Catalan, this work should facilitate future research on personality in the Catalan-speaking population.
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Peer-reviewed
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The most adequate approach for benchmarking web accessibility is manual expert evaluation supplemented by automatic analysis tools. But manual evaluation has a high cost and is impractical to be applied on large websites. In reality, there is no choice but to rely on automated tools when reviewing large web sites for accessibility. The question is: to what extent the results from automatic evaluation of a web site and individual web pages can be used as an approximation for manual results? This paper presents the initial results of an investigation aimed at answering this question. He have performed both manual and automatic evaluations of the accessibility of web pages of two sites and we have compared the results. In our data set automatically retrieved results could most definitely be used as an approximation manual evaluation results.
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This article describes the developmentof an Open Source shallow-transfer machine translation system from Czech to Polish in theApertium platform. It gives details ofthe methods and resources used in contructingthe system. Although the resulting system has quite a high error rate, it is still competitive with other systems.
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This paper discusses the qualitativecomparative evaluation performed on theresults of two machine translation systemswith different approaches to the processing ofmulti-word units. It proposes a solution forovercoming the difficulties multi-word unitspresent to machine translation by adopting amethodology that combines the lexicongrammar approach with OpenLogos ontologyand semantico-syntactic rules. The paper alsodiscusses the importance of a qualitativeevaluation metrics to correctly evaluate theperformance of machine translation engineswith regards to multi-word units.
Resumo:
Softcatalà is a non-profit associationcreated more than 10 years ago to fightthe marginalisation of the Catalan languagein information and communicationtechnologies. It has led the localisationof many applications and thecreation of a website which allows itsusers to translate texts between Spanishand Catalan using an external closed-sourcetranslation engine. Recently,the closed-source translation back-endhas been replaced by a free/open-sourcesolution completely managed by Softcatalà: the Apertium machine translationplatform and the ScaleMT web serviceframework. Thanks to the opennessof the new solution, it is possibleto take advantage of the huge amount ofusers of the Softcatalà translation serviceto improve it, using a series ofmethods presented in this paper. In addition,a study of the translations requestedby the users has been carriedout, and it shows that the translationback-end change has not affected theusage patterns.
Resumo:
This paper is a study of the concept of priority and its use together with the notion of hierarchy in academic writing and theoretical models of translation. Hierarchies and priorities can be implicit or explicit, prescribed, suggested or described. The paper starts, chronologically, wtih Nida and Levý’s hierarchical accounts of translation and follows their legacy in scholars as different as Newmark and Gutt. The concept of priorities is hinted at also in didactic models (Nord) as well as in norm-theoretical and accounts of translation (Toury and Chesterman) within Descriptive Translation Studies. All of these authors are analyzed and commented. The paper calls for a more systematic and straightforward account of translational priorities, and proposes a few conceptual tools that stem from this research model, including the concepts of ambition and richness of a translation. Finally, the paper concludes with an adaptation of Lakoff and Johnson’s view of prototypicality and its potential usefulness in research into and the understanding of translation.
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This is a case study of the Spanish dubbed version of Butch Cassidy and the Sundance Kid (George Roy Hill 1969) to illustrate and further develop the concept of L3 as a language that appears in source texts and their translations. L3 is distinguishable from the main language(s), L1 for the source text and L2 for the translation, based on a model proposed by Corrius and Zabalbeascoa 2011, and Corrius 2008. The study reveals various possible ways of rendering L3 in translation, in particular when L3 happens to coincide with L2. It also looks into the effect that certain translation solutions may have on intratextual translation and metatranslation.