Terminología bilingüe y documentación ad hoc para intérpretes de conferencias. Una aproximación metodológica basada en corpus

El intérprete de conferencias debe llevar a cabo un trabajo documental antes, durante y después de los eventos en los que presta sus servicios, independientemente de su subcompetencia extralingüística. Desafortunadamente, pocas son las propuestas metodológicas que se hayan planteado para que este profesional pueda realizar esta tarea de manera sistemática. En el presente artículo, repasamos algunos de los trabajos que se han referido a las posibilidades que tiene el intérprete de satisfacer sus necesidades informativas. Una vez reseñada la mencionada escasez de propuestas, presentamos, en un estudio de caso, una aproximación metodológica a este trabajo de documentación, fundamentada en la compilación de corpus paralelos ad hoc y la extracción terminológica en forma de glosarios.

Araknion: inducción de modelos lingüísticos a partir de corpora

El proyecto Araknion tiene como objetivo general dotar al español y al catalán de una infraestructura básica de recursos lingüísticos para el procesamiento semántico de corpus en el marco de la Web 2.0 sean de origen oral o escrito.

Sports anglicisms in Spanish dictionaries and corpora

For references, please quote the full paper as published in the above journal.

Opinion and generic question answering systems: a performance analysis

The importance of the new textual genres such as blogs or forum entries is growing in parallel with the evolution of the Social Web. This paper presents two corpora of blog posts in English and in Spanish, annotated according to the EmotiBlog annotation scheme. Furthermore, we created 20 factual and opinionated questions for each language and also the Gold Standard for their answers in the corpus. The purpose of our work is to study the challenges involved in a mixed fact and opinion question answering setting by comparing the performance of two Question Answering (QA) systems as far as mixed opinion and factual setting is concerned. The first one is open domain, while the second one is opinion-oriented. We evaluate separately the two systems in both languages and propose possible solutions to improve QA systems that have to process mixed questions.

Multilingual extension of a temporal expression normalizer using annotated corpora

This paper presents the automatic extension to other languages of TERSEO, a knowledge-based system for the recognition and normalization of temporal expressions originally developed for Spanish. TERSEO was first extended to English through the automatic translation of the temporal expressions. Then, an improved porting process was applied to Italian, where the automatic translation of the temporal expressions from English and from Spanish was combined with the extraction of new expressions from an Italian annotated corpus. Experimental results demonstrate how, while still adhering to the rule-based paradigm, the development of automatic rule translation procedures allowed us to minimize the effort required for porting to new languages. Relying on such procedures, and without any manual effort or previous knowledge of the target language, TERSEO recognizes and normalizes temporal expressions in Italian with good results (72% precision and 83% recall for recognition).

An hybrid parallel algorithm for solving tridiagonal linear systems versus the Wang’s method in a Cray T3D BSP computer

In this paper we describe an hybrid algorithm for an even number of processors based on an algorithm for two processors and the Overlapping Partition Method for tridiagonal systems. Moreover, we compare this hybrid method with the Partition Wang’s method in a BSP computer. Finally, we compare the theoretical computation cost of both methods for a Cray T3D computer, using the cost model that BSP model provides.

Sequential and parallel synchronous alternating iterative methods

The so-called parallel multisplitting nonstationary iterative Model A was introduced by Bru, Elsner, and Neumann [Linear Algebra and its Applications 103:175-192 (1988)] for solving a nonsingular linear system Ax = b using a weak nonnegative multisplitting of the first type. In this paper new results are introduced when A is a monotone matrix using a weak nonnegative multisplitting of the second type and when A is a symmetric positive definite matrix using a P -regular multisplitting. Also, nonstationary alternating iterative methods are studied. Finally, combining Model A and alternating iterative methods, two new models of parallel multisplitting nonstationary iterations are introduced. When matrix A is monotone and the multisplittings are weak nonnegative of the first or of the second type, both models lead to convergent schemes. Also, when matrix A is symmetric positive definite and the multisplittings are P -regular, the schemes are also convergent.

A reassessment of traditional lexicographical tools in the light of new corpora: sports Anglicisms in Spanish

There is no question nowadays as to the international and powerful status of English at a global scale and, consequently, as to its presence in non-English speaking countries at different levels. Linguistically speaking, English is one of the languages which have mostly influenced Spanish throughout its history and especially from the late 1960s. In this study, the impact of English on Spanish is considered in the language of sports; particularly, sports Anglicisms and false Anglicisms are analysed. Due attention is paid to the different forms that an Anglicism may adopt and to which of those forms are more widely accepted or rejected by prescriptivists and speakers at large, in the light of a contrastive analysis of their appearance in the Nuevo diccionario de anglicismos, the Diccionario de la Real Academia Española and the Corpus de Referencia del Español Actual.

A parallel method for impulsive image noise removal on hybrid CPU/GPU systems

A parallel algorithm for image noise removal is proposed. The algorithm is based on peer group concept and uses a fuzzy metric. An optimization study on the use of the CUDA platform to remove impulsive noise using this algorithm is presented. Moreover, an implementation of the algorithm on multi-core platforms using OpenMP is presented. Performance is evaluated in terms of execution time and a comparison of the implementation parallelised in multi-core, GPUs and the combination of both is conducted. A performance analysis with large images is conducted in order to identify the amount of pixels to allocate in the CPU and GPU. The observed time shows that both devices must have work to do, leaving the most to the GPU. Results show that parallel implementations of denoising filters on GPUs and multi-cores are very advisable, and they open the door to use such algorithms for real-time processing.

La traducción español-francés de locuciones preposicionales en el lenguaje comercial. Estudio comparativo basado en corpus

Il semble que peu d’importance ait été accordée à la langue générale dans la bibliographie sur la traduction économique bien qu’elle puisse en fait poser problème lors de sa traduction, tout au moins dans le cadre de la formation de traducteurs. Dans cet article nous traitons du comportement traductologique espagnol-français des locutions prépositionnelles. Nous nous pencherons d’abord sur les problèmes conceptuels de ce phénomène linguistique pour ensuite identifier et classer les locutions répertoriées dans notre corpus. Enfin, nous commentons leurs traductions. Les résultats peuvent être pris en considération, entre autres, dans l’enseignement de la traduction.

Parallel Computational Intelligence-Based Multi-Camera Surveillance System

In this work, we present a multi-camera surveillance system based on the use of self-organizing neural networks to represent events on video. The system processes several tasks in parallel using GPUs (graphic processor units). It addresses multiple vision tasks at various levels, such as segmentation, representation or characterization, analysis and monitoring of the movement. These features allow the construction of a robust representation of the environment and interpret the behavior of mobile agents in the scene. It is also necessary to integrate the vision module into a global system that operates in a complex environment by receiving images from multiple acquisition devices at video frequency. Offering relevant information to higher level systems, monitoring and making decisions in real time, it must accomplish a set of requirements, such as: time constraints, high availability, robustness, high processing speed and re-configurability. We have built a system able to represent and analyze the motion in video acquired by a multi-camera network and to process multi-source data in parallel on a multi-GPU architecture.

Parallel relaxed and extrapolated algorithms for computing PageRank

In this paper, parallel Relaxed and Extrapolated algorithms based on the Power method for accelerating the PageRank computation are presented. Different parallel implementations of the Power method and the proposed variants are analyzed using different data distribution strategies. The reported experiments show the behavior and effectiveness of the designed algorithms for realistic test data using either OpenMP, MPI or an hybrid OpenMP/MPI approach to exploit the benefits of shared memory inside the nodes of current SMP supercomputers.

Diacronia i neologia: canvi semàntic, subjectivació i representació del pensament. El català esmar, des de ‘taxar’ fins a ‘inferir’ i ‘imaginar’ i més enllà

L’estudi de la neologia és indestriable de l’estudi del canvi lingüístic i, doncs, de la diacronia. Ens proposem ací descriure el procés de canvi semàntic que va experimentar el verb esmar, forma patrimonial del llatí *adaestimare, paral·lela del cultisme estimar. Aquesta recerca es fonamenta en l’aprofitament dels corpus textuals i altres materials despullats manualment. Sobre aquests materials, s’ha assajat l’anàlisi de la subjectivació i de les inferències que proposa la teoria de la inferència invitada del canvi semàntic (= TIICS).

The use of corpora as translation resources: A study based on a survey of Spanish professional translators

The aim of this paper is to describe the use that professional translators make of corpora as translation resources. First, we briefly review the literature on translation practitioners’ use of corpora in the contexts of both translation training and professional translation. Then we present our survey-based study, analyse the uptake of corpora among Spanish translators and describe the use of this kind of translation resource. The results show that even if corpora are not as frequently used as other kinds of resources, such as dictionaries, there are professional translators who do use corpora, in a variety of ways, in their work. Additionally, non-users do not seem entirely sceptical about corpora. Against that backdrop, translator trainers are invited to continue to report on how corpora can be used as translation resources.

Improving drug discovery using a neural networks based parallel scoring function

Virtual Screening (VS) methods can considerably aid clinical research, predicting how ligands interact with drug targets. Most VS methods suppose a unique binding site for the target, but it has been demonstrated that diverse ligands interact with unrelated parts of the target and many VS methods do not take into account this relevant fact. This problem is circumvented by a novel VS methodology named BINDSURF that scans the whole protein surface to find new hotspots, where ligands might potentially interact with, and which is implemented in massively parallel Graphics Processing Units, allowing fast processing of large ligand databases. BINDSURF can thus be used in drug discovery, drug design, drug repurposing and therefore helps considerably in clinical research. However, the accuracy of most VS methods is constrained by limitations in the scoring function that describes biomolecular interactions, and even nowadays these uncertainties are not completely understood. In order to solve this problem, we propose a novel approach where neural networks are trained with databases of known active (drugs) and inactive compounds, and later used to improve VS predictions.