Post-abscission, pre-dispersal seeds of Digitalis purpurea remain in a developmental state that is not terminated by desiccation ex planta

Seed quality may be compromised if seeds are harvested before natural dispersal (shedding). It has been shown previously that slow or delayed drying can increase potential quality compared with immediate rapid drying. This study set out to investigate whether or not there is a critical moisture content, below which drying terminates maturation events for seeds harvested after mass maturity but before dispersal. Seeds of foxglove (Digitalis purpurea) in the post-abscission pre-dispersal phase were held at between 15 and 95 % RH for 4 or 8 d, with or without re-hydration to 95 % RH for a further 4 d, before drying to equilibrium at 15 % RH. In addition, dry seeds were primed for 48 h at -1 MPa. Subsequent seed longevity was assessed at 60 % RH and 45 degrees C. Rate of germination and longevity were improved by holding seeds at a wide range of humidities after harvest. Longevity was further improved by re-hydration at 95 % RH. Priming improved the longevity of the seeds dried immediately after harvest, but not of those first held at 95 % RH for 8 d prior to drying. Maturation continued ex planta in these post-abscission, pre-dispersal seeds of D. purpurea dried at 15-80 % RH at a rate correlated positively with RH (cf. ageing of mature seeds). Subsequent re-hydration at 95 % RH enabled a further improvement in quality. Priming seeds initially stored air-dry for 3 months also allowed maturation events to resume. However, once individual seeds within the population had reached maximum longevity, priming had a negative impact on their subsequent survival.

Using metrics from complex networks to evaluate machine translation

Establishing metrics to assess machine translation (MT) systems automatically is now crucial owing to the widespread use of MT over the web. In this study we show that such evaluation can be done by modeling text as complex networks. Specifically, we extend our previous work by employing additional metrics of complex networks, whose results were used as input for machine learning methods and allowed MT texts of distinct qualities to be distinguished. Also shown is that the node-to-node mapping between source and target texts (English-Portuguese and Spanish-Portuguese pairs) can be improved by adding further hierarchical levels for the metrics out-degree, in-degree, hierarchical common degree, cluster coefficient, inter-ring degree, intra-ring degree and convergence ratio. The results presented here amount to a proof-of-principle that the possible capturing of a wider context with the hierarchical levels may be combined with machine learning methods to yield an approach for assessing the quality of MT systems. (C) 2010 Elsevier B.V. All rights reserved.

Machine Translation and the Disruption of Foreign Language Learning Activities

This study examines the question of how language teachers in a highly technologyfriendly university environment view machine translation and the implications that this has for the personal learning environments of students. It brings an activity-theory perspective to the question, examining the ways that the introduction of new tools can disrupt the relationship between different elements in an activity system. This perspective opens up for an investigation of the ways that new tools have the potential to fundamentally alter traditional learning activities. In questionnaires and group discussions, respondents showed general agreement that although use of machine translation by students could be considered cheating, students are bound to use it anyway, and suggested that teachers focus on the kinds of skills students would need when using machine translation and design assignments and exams to practice and assess these skills. The results of the empirical study are used to reflect upon questions of what the roles of teachers and students are in a context where many of the skills that a person needs to be able to interact in a foreign language increasingly can be outsourced to laptops and smartphones.

Machine translation and the disruption of foreign language learning activities

This study examines the question of how language teachers in a highly technology-friendly university environment view machine translation and the implications that this has for the personal learning environments of students. It brings an activity-theory perspective to the question, examining the ways that the introduction of new tools can disrupt the relationship between different elements in an activity system. This perspective opens up for an investigation of the ways that new tools have the potential to fundamentally alter traditional learning activities. In questionnaires and group discussions, respondents showed general agreement that although use of machine translation by students could be considered cheating, students are bound to use it anyway, and suggested that teachers focus on the kinds of skills students would need when using machine translation and design assignments and exams to practice and assess these skills. The results of the empirical study are used to reflect upon questions of what the roles of teachers and students are in a context where many of the skills that a person needs to be able to interact in a foreign language increasingly can be outsourced to laptops and smartphones.

O texto adaptado à máquina: estratégias de controle autoral para implementação da tradução automática

Machine translation systems have been increasingly used for translation of large volumes of specialized texts. The efficiency of these systems depends directly on the implementation of strategies for controlling lexical use of source texts as a way to guarantee machine performance and, ultimately, human revision and post-edition work. This paper presents a brief history of application of machine translation, introduces the concept of lexicon and ambiguity and focuses on some of the lexical control strategies presently used, discussing their possible implications for the production and reading of specialized texts.

Realizzazione di un sistema di traduzione automatica di regole semantiche dall'italiano al francese.

Nell’ambito di questo progetto di tesi è stato studiato un sistema per la traduzione automatica, dall'italiano al francese, del contenuto di regole semantiche. Le regole in oggetto riguardano la categorizzazione di documenti secondo la tassonomia definita da IPTC.

Sottotitolaggio e traduzione automatica

La presente tesi analizza le principali caratteristiche di due tipi di traduzione: la traduzione audiovisiva, e in particolare il sottotitolaggio, e la traduzione automatica (TA). Obiettivo della nostra ricerca è stabilire quali risultati è possibile aspettarsi dall’impiego di sistemi di traduzione automatica appositamente sviluppati, nella creazione di sottotitoli di qualità professionale. Tale metodo avrebbe il potenziale vantaggio di velocizzare il processo traduttivo, riducendo in parte la pressione cui i sottotitolatori sono sottoposti, dovendo realizzare molte traduzioni in tempi troppo brevi, spesso a scapito della qualità finale del prodotto. Nel presente lavoro, il Capitolo 1 delinea le tappe principali della nascita e dello sviluppo della traduzione automatica, fino ad arrivare ai sistemi di TA più moderni. Nel Capitolo 2 vengono presentati i tipi principali di sistemi di traduzione automatica, con riferimento alle loro potenzialità e alle loro debolezze, soprattutto per quanto riguarda il loro impiego nel settore multimediale. Il Capitolo 3 riguarda la storia del sottotitolaggio, e le condizioni che hanno portato allo sviluppo e alla diffusione delle diverse modalità di traduzione audiovisiva, di cui il sottotitolaggio è una variante. Nel Capitolo 4 descriveremo le fasi principali di questo processo traduttivo, con particolare enfasi sull’importanza del contesto di arrivo e delle esigenze e aspettative dei futuri fruitori del testo finale. I Capitoli 5 e 6 presentano il lavoro di ricerca “sul campo”, svolto per raccogliere il parere di sottotitolatori professionisti e fansubber, attivi in Italia e all’estero, riguardo la possibilità di usare la TA nel loro lavoro. Infine, il capitolo conclusivo fornisce un commento sui risultati ottenuti, e sulle prospettive future riguardo la possibile apertura da parte del sottotitolaggio verso questa nuova tecnologia.

Discourse-level Annotation over Europarl for Machine Translation: Connectives and Pronouns

This paper describes methods and results for the annotation of two discourse-level phenomena, connectives and pronouns, over a multilingual parallel corpus. Excerpts from Europarl in English and French have been annotated with disambiguation information for connectives and pronouns, for about 3600 tokens. This data is then used in several ways: for cross-linguistic studies, for training automatic disambiguation software, and ultimately for training and testing discourse-aware statistical machine translation systems. The paper presents the annotation procedures and their results in detail, and overviews the first systems trained on the annotated resources and their use for machine translation.

Automatic Categorization for Improving Spanish into Spanish Sign Language Machine Translation

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.

Sentence selection for improving the tuning process of a statistical machine translation system

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%.

Phrase-based statistical machine translation: explanation of its processes and statistical models and evaluation of the English to Spanish translations produced

Statistical machine translation (SMT) is an approach to Machine Translation (MT) that uses statistical models whose parameter estimation is based on the analysis of existing human translations (contained in bilingual corpora). From a translation student’s standpoint, this dissertation aims to explain how a phrase-based SMT system works, to determine the role of the statistical models it uses in the translation process and to assess the quality of the translations provided that system is trained with in-domain goodquality corpora. To that end, a phrase-based SMT system based on Moses has been trained and subsequently used for the English to Spanish translation of two texts related in topic to the training data. Finally, the quality of this output texts produced by the system has been assessed through a quantitative evaluation carried out with three different automatic evaluation measures and a qualitative evaluation based on the Multidimensional Quality Metrics (MQM).