THE IMPACT OF THE ENGLISH ECONOMIC TERMS IN THE BUSINESS ENVIRONMENT

In terms of quantity, the English (American) influence in the economic language is striking, remarkable. The adjustment of these terms is brief, relative, which is not a factor favoring the assimilation of loans, but is permissible, in principle, for Anglicisms. In what concerns the need for these loans, it can be deemed that the demarcation between "necessary loans" and "luxury loans" is not yet solid. Low frequency or isolated Anglicisms may be classified into the second category (some may even affect proper specialized communication). Even if enough Anglicisms recorded in the economic press will not remain in Romanian, "the era of the Internet, of globalization" , we may consider a greater influence of English in the economy (perhaps similar to computer science).Anglicisms, economic terms, specialized communication

Automatic Recognition of Concurrent and Coupled Human Motion Sequences

We developed methods and algorithms for all parts of a motion recognition system, i. e. Feature Extraction, Motion Segmentation and Labeling, Motion Primitive and Context Modeling as well as Decoding. We collected several datasets to compare our proposed methods with the state-of-the-art in human motion recognition. The main contributions of this thesis are a structured functional motion decomposition and a flexible and scalable motion recognition system suitable for a Humanoid Robot

Speech Recognition by Composition of Weighted Finite Automata

We present a general framework based on weighted finite automata and weighted finite-state transducers for describing and implementing speech recognizers. The framework allows us to represent uniformly the information sources and data structures used in recognition, including context-dependent units, pronunciation dictionaries, language models and lattices. Furthermore, general but efficient algorithms can used for combining information sources in actual recognizers and for optimizing their application. In particular, a single composition algorithm is used both to combine in advance information sources such as language models and dictionaries, and to combine acoustic observations and information sources dynamically during recognition.Comment: 24 pages, uses psfig.st

Evaluating syntax-driven approaches to phrase extraction for MT

In this paper, we examine a number of different phrase segmentation approaches for Machine Translation and how they perform when used to supplement the translation model of a phrase-based SMT system. This work represents a summary of a number of years of research carried out at Dublin City University in which it has been found that improvements can be made using hybrid translation models. However, the level of improvement achieved is dependent on the amount of training data used. We describe the various approaches to phrase segmentation and combination explored, and outline a series of experiments investigating the relative merits of each method

The efects of peer corrective feedback trainning in face to face interaction and synchronousvideo-based computer-mediated comunication

Tesis (Profesor de Inglés para la Enseñanza Básica y Media y al grado académico de Licenciado en Educación)This quasi-experimental study was conducted in a private school, in Santiago, Chile, with four groups formed by 9th graders with the same L1 (Spanish) immersed in an EFL context. The purpose of the study was to examine ways in which the potential of peer interaction on learning is maximized. Specifically, the study examined two instructional techniques, both of which have been gaining increasing attention from second language acquisition researchers: (a) training learners how to correct each other (corrective feedback: CF), and (b) synchronous communicative interaction via video-based computer-mediated communication (SVCMC). Participants were divided into four groups depending on their experimental conditions. Group A (SVCMC+CF training) engaged in communicative peer interaction via SVCMC and received CF training. Group B (SVCMC-CF training) was given the same peer interaction tasks but did not receive any CF training. Groups C (FTF+CF training) and D (FTF-CF training) engaged in the same tasks in face-to-face in the classroom while only Group C received CF training. The intervention period lasted two weeks, consisting of four classes of 45 minutes for each of the four groups. The analysis involved (a) learners’ interactional behaviors, namely, language-related episodes, (b) their developmental outcomes with pre- and posttests focusing on past tense and locative usages, and (c) their perceptions based on exit questionnaire with close- and open-items. The results of this study reflected 3 main findings in peer interaction, corrective feedback, and SVCMC. With regard to interactional patterns (peer interaction), corrective feedback training promotes collaboration and so FTF environments, yet in SVCMC dominant patterns were more likely to arise. Meanwhile, CF training helped enhance learners’ language development as their results in the post-test were higher than in the pre-test and, in turn, SVCMC groups outperformed FTF groups. Concerning students’ perceptions, they overtly expressed positive beliefs regarding Peer Corrective Feedback and SVCMC activities. In short, clear differences were found among groups with different interventions resulting in distinct patterns, L2 development outcomes, and learner perceptions.Este estudio cuasi-experimental fue conducido en un colegio privado en Santiago de Chile, con cuatro grupos formados por estudiantes de primer año medio, cuya lengua nativa es el español. Los estudiantes estuvieron inmersos en un contexto EFL. El propósito del estudio fue examinar medios por las cuales el potencial de la interacción entre pares en el aprendizaje sea maximizado. Específicamente, este estudio examinó dos técnicas instructivas, las cuales han recibido recientemente atención paulatina de los investigadores en el campo de la adquisición de un segundo idioma: (a) capacitar a los estudiantes en como corregir a sus pares (retroalimentación), e (b) interacción comunicativa sincronizada a través de video conferencias (ICSV) mediadas por computadores. Los participantes fueron divididos en cuatro grupos según sus condiciones experimentales. El Grupo A (ICSV+ capacitación en retroalimentación) involucrado en interacción comunicativa— entre pares— a través de ICSV y recibieron instrucción en retroalimentación entre pares. Al Grupo B (ICSV – capacitación en retroalimentación) se le dio las mismas tareas, pero no recibió capacitación en retroalimentación. El Grupo C (cara a cara + capacitación en retroalimentación) y el Grupo D (cara a cara – capacitación en retroalimentación) participaron en las mismas tareas cara a cara en la sala de clases mientras que solo el Grupo C recibió capacitación en retroalimentación. El periodo de intervención fue de 2 semanas, compuesto de 4 clases de 45 min para cada uno de los grupos. Este análisis involucró (a) comportamientos interaccionales de los estudiantes, es decir, episodios relacionados con el lenguaje, (b) los resultados que reflejaron el desarrollo del lenguaje de los estudiantes fueron obtenidos mediante una evaluación previa a la intervención y otra posterior a la intervención; las evaluaciones se enfocaron en el uso del pasado simple y locativos, finalmente (c) las percepciones de los estudiantes obtenidas mediante un cuestionario de preguntas cerradas y abiertas. Los resultados de este estudio reflejaron 3 hallazgos principales en cuanto a interacción entre pares, retroalimentación, e ICSV. En cuanto a los patrones interacciónales (interacción entre pares), la retroalimentación y la comunicación cara a cara resultaron promover la colaboración, a diferencia de ICSV en la cual los patrones dominantes tuvieron más probabilidades de surgir. Mientras tanto, la capacitación en retroalimentación ayudó al mejoramiento del desarrollo del lenguaje de los estudiantes ya que sus resultados a lo largo de las evaluaciones pre y post presentaron un alza y, en consecuencia, los grupos que interactuaron a través de ICSV superaron a los grupos que interactuaron cara a cara. Tomando en cuenta las percepciones de los estudiantes, ellos expresaron abiertamente ideas positivas en cuanto a las actividades la capacitación en retroalimentación e ICSV. En resumen, diferencias claras fueron encontradas entre los grupos con diferentes intervenciones resultando en distintos patrones de interacción, resultados en el desarrollo del lenguaje, y percepciones de los estudiantes

Decoding Choice Encodings

We study two encodings of the asynchronous pi-calculus with input-guarded choice into its choice-free fragment. One encoding is divergence-free, but refines the atomic commitment of choice into gradual commitment. The other preserves atomicity, but introduces divergence. The divergent encoding is fully abstract with respect to weak bisimulation, but the more natural divergence-free encoding is not. Instead, we show that it is fully abstract with respect to coupled simulation, a slightly coarser - but still coinductively defined - equivalence that does not enforce bisimilarity of internal branching decisions. The correctness proofs for the two choice encodings introduce a novel proof technique exploiting the properties of explicit decodings from translations to source terms

Resourcing machine translation with parallel treebanks

The benefits of syntax-based approaches to data-driven machine translation (MT) are clear: given the right model, a combination of hierarchical structure, constituent labels and morphological information can be exploited to produce more fluent, grammatical translation output. This has been demonstrated by the recent shift in research focus towards such linguistically motivated approaches. However, one issue facing developers of such models that is not encountered in the development of state-of-the-art string-based statistical MT (SMT) systems is the lack of available syntactically annotated training data for many languages. In this thesis, we propose a solution to the problem of limited resources for syntax-based MT by introducing a novel sub-sentential alignment algorithm for the induction of translational equivalence links between pairs of phrase structure trees. This algorithm, which operates on a language pair-independent basis, allows for the automatic generation of large-scale parallel treebanks which are useful not only for machine translation, but also across a variety of natural language processing tasks. We demonstrate the viability of our automatically generated parallel treebanks by means of a thorough evaluation process during which they are compared to a manually annotated gold standard parallel treebank both intrinsically and in an MT task. Following this, we hypothesise that these parallel treebanks are not only useful in syntax-based MT, but also have the potential to be exploited in other paradigms of MT. To this end, we carry out a large number of experiments across a variety of data sets and language pairs, in which we exploit the information encoded within the parallel treebanks in various components of phrase-based statistical MT systems. We demonstrate that improvements in translation accuracy can be achieved by enhancing SMT phrase tables with linguistically motivated phrase pairs extracted from a parallel treebank, while showing that a number of other features in SMT can also be supplemented with varying degrees of effectiveness. Finally, we examine ways in which synchronous grammars extracted from parallel treebanks can improve the quality of translation output, focussing on real translation examples from a syntax-based MT system