18 resultados para TRANSLATION EFFICIENCIES


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High efficiency solar cells working under ultra-high concentrations (>;1000X) have been shown to be a promising solution to decrease the cost of PV electricity, increase the efficiency and circumvent the material availability restrictions for massive PV penetration. A detailed analysis of the limitations of our current triple junction solar cell (36.2% at 700X), in the quest to maximize efficiency at 1000X, shows that the main improvements to tackle are: a) implementation of a high band gap tunnel junction; b) increase the band gap of the top cell; c) fine current matching tune; d) enhancement of the front contact process. This constitutes our roadmap to reach an efficiency over 41%

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This paper describes a preprocessing module for improving the performance of a Spanish into Spanish Sign Language (Lengua de Signos Espanola: LSE) translation system when dealing with sparse training data. This preprocessing module replaces Spanish words with associated tags. The list with Spanish words (vocabulary) and associated tags used by this module is computed automatically considering those signs that show the highest probability of being the translation of every Spanish word. This automatic tag extraction has been compared to a manual strategy achieving almost the same improvement. In this analysis, several alternatives for dealing with non-relevant words have been studied. Non-relevant words are Spanish words not assigned to any sign. The preprocessing module has been incorporated into two well-known statistical translation architectures: a phrase-based system and a Statistical Finite State Transducer (SFST). This system has been developed for a specific application domain: the renewal of Identity Documents and Driver's License. In order to evaluate the system a parallel corpus made up of 4080 Spanish sentences and their LSE translation has been used. The evaluation results revealed a significant performance improvement when including this preprocessing module. In the phrase-based system, the proposed module has given rise to an increase in BLEU (Bilingual Evaluation Understudy) from 73.8% to 81.0% and an increase in the human evaluation score from 0.64 to 0.83. In the case of SFST, BLEU increased from 70.6% to 78.4% and the human evaluation score from 0.65 to 0.82.

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This paper proposes the use of Factored Translation Models (FTMs) for improving a Speech into Sign Language Translation System. These FTMs allow incorporating syntactic-semantic information during the translation process. This new information permits to reduce significantly the translation error rate. This paper also analyses different alternatives for dealing with the non-relevant words. The speech into sign language translation system has been developed and evaluated in a specific application domain: the renewal of Identity Documents and Driver’s License. The translation system uses a phrase-based translation system (Moses). The evaluation results reveal that the BLEU (BiLingual Evaluation Understudy) has improved from 69.1% to 73.9% and the mSER (multiple references Sign Error Rate) has been reduced from 30.6% to 24.8%.

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This paper describes a categorization module for improving the performance of a Spanish into Spanish Sign Language (LSE) translation system. This categorization module replaces Spanish words with associated tags. When implementing this module, several alternatives for dealing with non-relevant words have been studied. Non-relevant words are Spanish words not relevant in the translation process. The categorization module has been incorporated into a phrase-based system and a Statistical Finite State Transducer (SFST). The evaluation results reveal that the BLEU has increased from 69.11% to 78.79% for the phrase-based system and from 69.84% to 75.59% for the SFST.

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This paper describes the UPM system for translation task at the EMNLP 2011 workshop on statistical machine translation (http://www.statmt.org/wmt11/), and it has been used for both directions: Spanish-English and English-Spanish. This system is based on Moses with two new modules for pre and post processing the sentences. The main contribution is the method proposed (based on the similarity with the source language test set) for selecting the sentences for training the models and adjusting the weights. With system, we have obtained a 23.2 BLEU for Spanish-English and 21.7 BLEU for EnglishSpanish

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Ontologies and taxonomies are widely used to organize concepts providing the basis for activities such as indexing, and as background knowledge for NLP tasks. As such, translation of these resources would prove useful to adapt these systems to new languages. However, we show that the nature of these resources is significantly different from the "free-text" paradigm used to train most statistical machine translation systems. In particular, we see significant differences in the linguistic nature of these resources and such resources have rich additional semantics. We demonstrate that as a result of these linguistic differences, standard SMT methods, in particular evaluation metrics, can produce poor performance. We then look to the task of leveraging these semantics for translation, which we approach in three ways: by adapting the translation system to the domain of the resource; by examining if semantics can help to predict the syntactic structure used in translation; and by evaluating if we can use existing translated taxonomies to disambiguate translations. We present some early results from these experiments, which shed light on the degree of success we may have with each approach

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The limiting efficiencies of GaAs solar cells when used under concentrated sunlight are calculated. The benefits to be expected from applying techniques which restrict the angle of acceptance of the cell are determined. It is concluded that when the acceptance angle is restricted the emission of the luminescent photons and therefore the associated current loss are reduced. A limiting efficiency close to 39% results for concentration ratios of about 1000 suns AM1.5 direct. For lower concentration ratios, the limiting efficiency decreases if Auger recombination is also taken into account

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Semantic Web aims to allow machines to make inferences using the explicit conceptualisations contained in ontologies. By pointing to ontologies, Semantic Web-based applications are able to inter-operate and share common information easily. Nevertheless, multilingual semantic applications are still rare, owing to the fact that most online ontologies are monolingual in English. In order to solve this issue, techniques for ontology localisation and translation are needed. However, traditional machine translation is difficult to apply to ontologies, owing to the fact that ontology labels tend to be quite short in length and linguistically different from the free text paradigm. In this paper, we propose an approach to enhance machine translation of ontologies based on exploiting the well-structured concept descriptions contained in the ontology. In particular, our approach leverages the semantics contained in the ontology by using Cross Lingual Explicit Semantic Analysis (CLESA) for context-based disambiguation in phrase-based Statistical Machine Translation (SMT). The presented work is novel in the sense that application of CLESA in SMT has not been performed earlier to the best of our knowledge.

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The Andorra family of languages (which includes the Andorra Kernel Language -AKL) is aimed, in principie, at simultaneously supporting the programming styles of Prolog and committed choice languages. On the other hand, AKL requires a somewhat detailed specification of control by the user. This could be avoided by programming in Prolog to run on AKL. However, Prolog programs cannot be executed directly on AKL. This is due to a number of factors, from more or less trivial syntactic differences to more involved issues such as the treatment of cut and making the exploitation of certain types of parallelism possible. This paper provides basic guidelines for constructing an automatic compiler of Prolog programs into AKL, which can bridge those differences. In addition to supporting Prolog, our style of translation achieves independent and-parallel execution where possible, which is relevant since this type of parallel execution preserves, through the translation, the user-perceived "complexity" of the original Prolog program.

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The Andorra Kernel language scheme was aimed, in principle, at simultaneously supporting the programming styles of Prolog and committed choice languages. Within the constraint programming paradigm, this family of languages could also in principle support the concurrent constraint paradigm. This happens for the Agents Kernel Language (AKL). On the other hand, AKL requires a somewhat detailed specification of control by the user. This could be avoided by programming in CLP to run on AKL. However, CLP programs cannot be executed directly on AKL. This is due to a number of factors, from more or less trivial syntactic differences to more involved issues such as the treatment of cut and making the exploitation of certain types of parallelism possible. This paper provides a translation scheme which is a basis of an automatic compiler of CLP programs into AKL, which can bridge those differences. In addition to supporting CLP, our style of translation achieves independent and-parallel execution where possible, which is relevant since this type of parallel execution preserves, through the translation, the user-perceived "complexity" of the original program.

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This paper describes the design, development and field evaluation of a machine translation system from Spanish to Spanish Sign Language (LSE: Lengua de Signos Española). The developed system focuses on helping Deaf people when they want to renew their Driver’s License. The system is made up of a speech recognizer (for decoding the spoken utterance into a word sequence), a natural language translator (for converting a word sequence into a sequence of signs belonging to the sign language), and a 3D avatar animation module (for playing back the signs). For the natural language translator, three technological approaches have been implemented and evaluated: an example-based strategy, a rule-based translation method and a statistical translator. For the final version, the implemented language translator combines all the alternatives into a hierarchical structure. This paper includes a detailed description of the field evaluation. This evaluation was carried out in the Local Traffic Office in Toledo involving real government employees and Deaf people. The evaluation includes objective measurements from the system and subjective information from questionnaires. The paper details the main problems found and a discussion on how to solve them (some of them specific for LSE).

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The electronic properties and the low environmental impact of Cu 3 BiS 3 make this compound a promising material for low-cost thin film solar cell technology. From the first principles, the electronic properties of the isoelectronic substitution of S by O in Cu 3 BiS 3 have been obtained using two different exchange-correlation potentials. This compound has an acceptor level below the conduction band, which modifies the opto-electronic properties with respect to the host semiconductor. In order to analyze a possible efficiency increment with respect to the host semiconductor, we have calculated the maximum efficiency of this photovoltaic absorber material.

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Este artículo describe una estrategia de selección de frases para hacer el ajuste de un sistema de traducción estadístico basado en el decodificador Moses que traduce del español al inglés. En este trabajo proponemos dos posibilidades para realizar esta selección de las frases del corpus de validación que más se parecen a las frases que queremos traducir (frases de test en lengua origen). Con esta selección podemos obtener unos mejores pesos de los modelos para emplearlos después en el proceso de traducción y, por tanto, mejorar los resultados. Concretamente, con el método de selección basado en la medida de similitud propuesta en este artículo, mejoramos la medida BLEU del 27,17% con el corpus de validación completo al 27,27% seleccionando las frases para el ajuste. Estos resultados se acercan a los del experimento ORACLE: se utilizan las mismas frases de test para hacer el ajuste de los pesos. En este caso, el BLEU obtenido es de 27,51%.

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En la conferencia se expone la situación en España de los riegos a presión considerando los condicionantes de escasez de agua y el precio de la energía.

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This paper proposes an architecture, based on statistical machine translation, for developing the text normalization module of a text to speech conversion system. The main target is to generate a language independent text normalization module, based on data and flexible enough to deal with all situa-tions presented in this task. The proposed architecture is composed by three main modules: a tokenizer module for splitting the text input into a token graph (tokenization), a phrase-based translation module (token translation) and a post-processing module for removing some tokens. This paper presents initial exper-iments for numbers and abbreviations. The very good results obtained validate the proposed architecture.