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Current Search:
All of 'Machine' and 'translating' in all fields;
259 items found
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Displaying Results 76 - 100 of 259 on page 4 of 11
Marked
Mark
MATREX: the DCU MT system for WMT 2010
(2010)
Penkale, Sergio; Haque, Rejwanul; Dandapat, Sandipan; Banerjee, Pratyush; Srivastava, A...
MATREX: the DCU MT system for WMT 2010
(2010)
Penkale, Sergio; Haque, Rejwanul; Dandapat, Sandipan; Banerjee, Pratyush; Srivastava, Ankit K.; Du, Jinhua; Pecina, Pavel; Kumar Naskar, Sudip; Forcada, Mikel; Way, Andy
Abstract:
This paper describes the DCU machine translation system in the evaluation campaign of the Joint Fifth Workshop on Statistical Machine Translation and Metrics in ACL-2010. We describe the modular design of our multi-engine machine translation (MT) system with particular focus on the components used in this participation. We participated in the English–Spanish and English–Czech translation tasks, in which we employed our multiengine architecture to translate. We also participated in the system combination task which was carried out by the MBR decoder and confusion network decoder.
http://doras.dcu.ie/15794/
Marked
Mark
Automatic acquisition of named entities for rule-based machine translation
(2011)
Toral, Antonio; Way, Andy
Automatic acquisition of named entities for rule-based machine translation
(2011)
Toral, Antonio; Way, Andy
Abstract:
This paper proposes to enrich RBMT dictionaries with Named Entities (NEs) automatically acquired from Wikipedia. The method is applied to the Apertium English–Spanish system and its performance compared to that of Apertium with and without handtagged NEs. The system with automatic NEs outperforms the one without NEs, while results vary when compared to a system with handtagged NEs (results are comparable for Spanish! English but slightly worst for English!Spanish). Apart from that, adding automatic NEs contributes to decreasing the amount of unknown terms by more than 10%.
http://doras.dcu.ie/16153/
Marked
Mark
MATREX: the DCU MT System for WMT 2008
(2008)
Tinsley, John; Ma, Yanjun; Ozdowska, Sylwia; Way, Andy
MATREX: the DCU MT System for WMT 2008
(2008)
Tinsley, John; Ma, Yanjun; Ozdowska, Sylwia; Way, Andy
Abstract:
In this paper, we give a description of the machine translation system developed at DCU that was used for our participation in the evaluation campaign of the Third Workshop on Statistical Machine Translation at ACL 2008. We describe the modular design of our data driven MT system with particular focus on the components used in this participation. We also describe some of the significant modules which were unused in this task. We participated in the EuroParl task for the following translation directions: Spanish–English and French–English, in which we employed our hybrid EBMT-SMT architecture to translate. We also participated in the Czech–English News and News Commentary tasks which represented a previously untested language pair for our system. We report results on the provided development and test sets.
http://doras.dcu.ie/559/
Marked
Mark
Recycling texts: human evaluation of example-based machine translation subtitles for DVD
(2009)
Flanagan, Marian
Recycling texts: human evaluation of example-based machine translation subtitles for DVD
(2009)
Flanagan, Marian
Abstract:
This project focuses on translation reusability in audiovisual contexts. Specifically, the project seeks to establish (1) whether target language subtitles produced by an EBMT system are considered intelligible and acceptable by viewers of movies on DVD, and (2)whether a relationship exists between the ‘profiles’ of corpora used to train an EBMT system, on the one hand, and viewers’ judgements of the intelligibility and acceptability of the subtitles produced by the system, on the other. The impact of other factors, namely: whether movie-viewing subjects have knowledge of the soundtrack language; subjects’ linguistic background; and subjects’ prior knowledge of the (Harry Potter) movie clips viewed; is also investigated. Corpus profiling is based on measurements (partly using corpus-analysis tools) of three characteristics of the corpora used to train the EBMT system: the number of source language repetitions they contain; the size of the corpus; and the homogeneity of the corpus (...
http://doras.dcu.ie/14842/
Marked
Mark
Hybrid rule-based - example-based MT: feeding apertium with sub-sentential translation units
(2009)
Sánchez-Martínez, Felipe; Forcada, Mikel L.; Way, Andy
Hybrid rule-based - example-based MT: feeding apertium with sub-sentential translation units
(2009)
Sánchez-Martínez, Felipe; Forcada, Mikel L.; Way, Andy
Abstract:
This paper describes a hybrid machine translation (MT) approach that consists of integrating bilingual chunks (sub-sentential translation units) obtained from parallel corpora into an MT system built using the Apertium free/open-source rule-based machine translation platform, which uses a shallow-transfer translation approach. In the integration of bilingual chunks, special care has been taken so as not to break the application of the existing Apertium structural transfer rules, since this would increase the number of ungrammatical translations. The method consists of (i) the application of a dynamic-programming algorithm to compute the best translation coverage of the input sentence given the collection of bilingual chunks available; (ii) the translation of the input sentence as usual by Apertium; and (iii) the application of a language model to choose one of the possible translations for each of the bilingual chunks detected. Results are reported for the translation from English-t...
http://doras.dcu.ie/15153/
Marked
Mark
Using percolated dependencies for phrase extraction in SMT
(2009)
Srivastava, Ankit K.; Way, Andy
Using percolated dependencies for phrase extraction in SMT
(2009)
Srivastava, Ankit K.; Way, Andy
Abstract:
Statistical Machine Translation (SMT) systems rely heavily on the quality of the phrase pairs induced from large amounts of training data. Apart from the widely used method of heuristic learning of n-gram phrase translations from word alignments, there are numerous methods for extracting these phrase pairs. One such class of approaches uses translation information encoded in parallel treebanks to extract phrase pairs. Work to date has demonstrated the usefulness of translation models induced from both constituency structure trees and dependency structure trees. Both syntactic annotations rely on the existence of natural language parsers for both the source and target languages. We depart from the norm by directly obtaining dependency parses from constituency structures using head percolation tables. The paper investigates the use of aligned chunks induced from percolated dependencies in French–English SMT and contrasts it with the aforementioned extracted phrases. We observe that ad...
http://doras.dcu.ie/15152/
Marked
Mark
F-structure transfer-based statistical machine translation
(2009)
Graham, Yvette; van Genabith, Josef; Bryl, Anton
F-structure transfer-based statistical machine translation
(2009)
Graham, Yvette; van Genabith, Josef; Bryl, Anton
Abstract:
In this paper, we describe a statistical deep syntactic transfer decoder that is trained fully automatically on parsed bilingual corpora. Deep syntactic transfer rules are induced automatically from the f-structures of a LFG parsed bitext corpus by automatically aligning local f-structures, and inducing all rules consistent with the node alignment. The transfer decoder outputs the n-best TL f-structures given a SL f-structure as input by applying large numbers of transfer rules and searching for the best output using a log-linear model to combine feature scores. The decoder includes a fully integrated dependency-based tri-gram language model. We include an experimental evaluation of the decoder using different parsing disambiguation resources for the German data to provide a comparison of how the system performs with different German training and test parses.
http://doras.dcu.ie/15170/
Marked
Mark
MATREX: the DCU MT system for WMT 2009
(2009)
Du, Jinhua; He, Yifan; Penkale, Sergio; Way, Andy
MATREX: the DCU MT system for WMT 2009
(2009)
Du, Jinhua; He, Yifan; Penkale, Sergio; Way, Andy
Abstract:
In this paper, we describe the machine translation system in the evaluation campaign of the Fourth Workshop on Statistical Machine Translation at EACL 2009. We describe the modular design of our multi-engine MT system with particular focus on the components used in this participation. We participated in the translation task for the following translation directions: French–English and English–French, in which we employed our multi-engine architecture to translate. We also participated in the system combination task which was carried out by the MBR decoder and Confusion Network decoder. We report results on the provided development and test sets.
http://doras.dcu.ie/15166/
Marked
Mark
Automatic evaluation of generation and parsing for machine translation with automatically acquired transfer rules
(2007)
Graham, Yvette; Hogan, Deirdre; van Genabith, Josef
Automatic evaluation of generation and parsing for machine translation with automatically acquired transfer rules
(2007)
Graham, Yvette; Hogan, Deirdre; van Genabith, Josef
Abstract:
This paper presents a new method of evaluation for generation and parsing components of transfer-based MT systems where the transfer rules have been automatically acquired from parsed sentence-aligned bitext corpora. The method provides a means of quantifying the upper bound imposed on the MT system by the quality of the parsing and generation technologies for the target language. We include experiments to calculate this upper bound for both handcrafted and automatically induced parsing and generation technologies currently in use by transfer-based MT systems.
http://doras.dcu.ie/15210/
Marked
Mark
A cluster-based representation for multi-system MT evaluation
(2007)
Stroppa, Nicolas; Owczarzak, Karolina; Way, Andy
A cluster-based representation for multi-system MT evaluation
(2007)
Stroppa, Nicolas; Owczarzak, Karolina; Way, Andy
Abstract:
Automatic evaluation metrics are often used to compare the quality of different systems. However, a small difference between the scores of two systems does not necessary reflect a real difference between their performance. Because such a difference can be significant or only due to chance, it is inadvisable to use a hard ranking to represent the evaluation of multiple systems. In this paper, we propose a cluster-based representation for quality ranking of Machine Translation systems. A comparison of rankings produced by clustering based on automatic MT evaluation metrics with those based on human judgements shows that such interpretation of automatic metric scores provides dependable means of ordering MT systems with respect to their quality. We report experimental results comparing clusterings produced by BLEU, NIST, METEOR, and GTM with those derived from human judgement (of adequacy and fluency) on the IWSLT-2006 evaluation campaign data.
http://doras.dcu.ie/15227/
Marked
Mark
Capturing translational divergences with a statistical tree-to-tree aligner
(2007)
Hearne, Mary; Tinsley, John; Zhechev, Ventsislav; Way, Andy
Capturing translational divergences with a statistical tree-to-tree aligner
(2007)
Hearne, Mary; Tinsley, John; Zhechev, Ventsislav; Way, Andy
Abstract:
Parallel treebanks, which comprise paired source-target parse trees aligned at sub-sentential level, could be useful for many applications, particularly data-driven machine translation. In this paper, we focus on how translational divergences are captured within a parallel treebank using a fully automatic statistical tree-to-tree aligner. We observe that while the algorithm performs well at the phrase level, performance on lexical-level alignments is compromised by an inappropriate bias towards coverage rather than precision. This preference for high precision rather than broad coverage in terms of expressing translational divergences through tree-alignment stands in direct opposition to the situation for SMT word-alignment models. We suggest that this has implications not only for tree-alignment itself but also for the broader area of induction of syntaxaware models for SMT.
http://doras.dcu.ie/15223/
Marked
Mark
A memory-based classification approach to marker-based EBMT
(2007)
van den Bosch, Antal; Stroppa, Nicolas; Way, Andy
A memory-based classification approach to marker-based EBMT
(2007)
van den Bosch, Antal; Stroppa, Nicolas; Way, Andy
Abstract:
We describe a novel approach to example-based machine translation that makes use of marker-based chunks, in which the decoder is a memory-based classifier. The classifier is trained to map trigrams of source-language chunks onto trigrams of target-language chunks; then, in a second decoding step, the predicted trigrams are rearranged according to their overlap. We present the first results of this method on a Dutch-to-English translation system using Europarl data. Sparseness of the class space causes the results to lag behind a baseline phrase-based SMT system. In a further comparison, we also apply the method to a word-aligned version of the same data, and report a smaller difference with a word-based SMT system. We explore the scaling abilities of the memory-based approach, and observe linear scaling behavior in training and classification speed and memory costs, and loglinear BLEU improvements in the amount of training examples.
http://doras.dcu.ie/15267/
Marked
Mark
The DCU machine translation system
(2006)
Stroppa, Nicolas; Way, Andy
The DCU machine translation system
(2006)
Stroppa, Nicolas; Way, Andy
http://doras.dcu.ie/15286/
Marked
Mark
Example-based controlled translation
(2004)
Gough, Nano; Way, Andy
Example-based controlled translation
(2004)
Gough, Nano; Way, Andy
Abstract:
The first research on integrating controlled language data in an Example-Based Machine Translation (EBMT) system was published in [Gough & Way, 2003]. We improve on their sub-sentential alignment algorithm to populate the system’s databases with more than six times as many potentially useful fragments. Together with two simple novel improvements—correcting mistranslations in the lexicon, and allowing multiple translations in the lexicon—translation quality improves considerably when target language translations are constrained. We also develop the first EBMT system which attempts to filter the source language data using controlled language specifications. We provide detailed automatic and human evaluations of a number of experiments carried out to test the quality of the system. We observe that our system outperforms Logomedia in a number of tests. Finally, despite conflicting results from different automatic evaluation metrics, we observe a preference for controlling the source...
http://doras.dcu.ie/15306/
Marked
Mark
Maximising TM performance through sub-tree alignment and SMT
(2010)
Zhechev, Ventsislav ; van Genabith, Josef
Maximising TM performance through sub-tree alignment and SMT
(2010)
Zhechev, Ventsislav ; van Genabith, Josef
Abstract:
With the steadily increasing demand for high quality translation, the localisation industry is constantly searching for technologies that would increase translator throughput, in particular focusing on the use of high-quality Statistical Machine Translation (SMT) supplementing the established Translation Memory (TM) technology. In this paper, we present a novel modular approach that utilises state-of-the-art sub-tree alignment and SMT techniques to turn the fuzzy matches from a TM into near perfect translations. Rather than relegate SMT to a last-resort status where it is only used should the TM system fail to produce the desired output, for us SMT is an integral part of the translation process that we rely on to obtain high-quality results. We show that the presented system consistently produces better quality output than the TM and performs on par or better than the standalone SMT system.
http://doras.dcu.ie/16019/
Marked
Mark
The DCU machine translation systems for IWSLT 2010
(2010)
Almaghout, Hala; Jiang, Jie; Way, Andy
The DCU machine translation systems for IWSLT 2010
(2010)
Almaghout, Hala; Jiang, Jie; Way, Andy
http://doras.dcu.ie/16157/
Marked
Mark
CCG augmented hierarchical phrase based machine-translation
(2010)
Almaghout, Hala; Jiang, Jie; Way, Andy
CCG augmented hierarchical phrase based machine-translation
(2010)
Almaghout, Hala; Jiang, Jie; Way, Andy
http://doras.dcu.ie/16156/
Marked
Mark
Word alignment and smoothing methods in statistical machine translation: Noise, prior knowledge and overfitting
(2012)
Okita, Tsuyoshi
Word alignment and smoothing methods in statistical machine translation: Noise, prior knowledge and overfitting
(2012)
Okita, Tsuyoshi
Abstract:
This thesis discusses how to incorporate linguistic knowledge into an SMT system. Although one important category of linguistic knowledge is that obtained by a constituent / dependency parser, a POS / super tagger, and a morphological analyser, linguistic knowledge here includes larger domains than this: Multi-Word Expressions, Out-Of-Vocabulary words, paraphrases, lexical semantics (or non-literal translations), named-entities, coreferences, and transliterations. The first discussion is about word alignment where we propose a MWE-sensitive word aligner. The second discussion is about the smoothing methods for a language model and a translation model where we propose a hierarchical Pitman-Yor process-based smoothing method. The common grounds for these discussion are the examination of three exceptional cases from real-world data: the presence of noise, the availability of prior knowledge, and the problem of underfitting. Notable characteristics of this design are the careful usage...
http://doras.dcu.ie/16759/
Marked
Mark
Evaluating syntax-driven approaches to phrase extraction for MT
(2009)
Srivastava, Ankit; Penkale, Sergio; Groves, Declan; Tinsley, John
Evaluating syntax-driven approaches to phrase extraction for MT
(2009)
Srivastava, Ankit; Penkale, Sergio; Groves, Declan; Tinsley, John
Abstract:
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.
http://doras.dcu.ie/15151/
Marked
Mark
A review of EBMT using proportional analogies
(2009)
Somers, Harold; Dandapat, Sandipan; Naskar, Sudip Kumar
A review of EBMT using proportional analogies
(2009)
Somers, Harold; Dandapat, Sandipan; Naskar, Sudip Kumar
Abstract:
Some years ago a number of papers reported an experimental implementation of Example Based Machine Translation (EBMT) using Proportional Analogy. This approach, a type of analogical learning, was attractive because of its simplicity; and the papers reported considerable success with the method. This paper reviews what we believe to be the totality of research reported using this method, as an introduction to our own experiments in this framework, reported in a companion paper. We report first some lack of clarity in the previously published work, and then report our findings that the purity of the proportional analogy approach imposes huge run-time complexity for the EBMT task even when heuristics as hinted at in the original literature are applied to reduce the amount of computation.
http://doras.dcu.ie/15149/
Marked
Mark
Hand in hand: automatic sign Language to English translation
(2007)
Stein, Daniel; Dreuw, Philippe; Ney, Hermann; Morrissey, Sara; Way, Andy
Hand in hand: automatic sign Language to English translation
(2007)
Stein, Daniel; Dreuw, Philippe; Ney, Hermann; Morrissey, Sara; Way, Andy
Abstract:
In this paper, we describe the first data-driven automatic sign-language-to- speech translation system. While both sign language (SL) recognition and translation techniques exist, both use an intermediate notation system not directly intelligible for untrained users. We combine a SL recognizing framework with a state-of-the-art phrase-based machine translation (MT) system, using corpora of both American Sign Language and Irish Sign Language data. In a set of experiments we show the overall results and also illustrate the importance of including a vision-based knowledge source in the development of a complete SL translation system.
http://doras.dcu.ie/15224/
Marked
Mark
Controlled generation in example-based machine translation
(2003)
Gough, Nano; Way, Andy
Controlled generation in example-based machine translation
(2003)
Gough, Nano; Way, Andy
Abstract:
The theme of controlled translation is currently in vogue in the area of MT. Recent research (Sch¨aler et al., 2003; Carl, 2003) hypothesises that EBMT systems are perhaps best suited to this challenging task. In this paper, we present an EBMT system where the generation of the target string is filtered by data written according to controlled language specifications. As far as we are aware, this is the only research available on this topic. In the field of controlled language applications, it is more usual to constrain the source language in this way rather than the target. We translate a small corpus of controlled English into French using the on-line MT system Logomedia, and seed the memories of our EBMT system with a set of automatically induced lexical resources using the Marker Hypothesis as a segmentation tool. We test our system on a large set of sentences extracted from a Sun Translation Memory, and provide both an automatic and a human evaluation. For comparative purposes, ...
http://doras.dcu.ie/15312/
Marked
Mark
An assessment of appropriate sign language representation for machine translation in the healthcare domain
(2009)
Morrissey, Sara
An assessment of appropriate sign language representation for machine translation in the healthcare domain
(2009)
Morrissey, Sara
http://doras.dcu.ie/15362/
Marked
Mark
The impact of source-side syntactic reordering on hierarchical phrase-based SMT
(2010)
Way, Andy; Du, Jinhua
The impact of source-side syntactic reordering on hierarchical phrase-based SMT
(2010)
Way, Andy; Du, Jinhua
Abstract:
Syntactic reordering has been demonstrated to be helpful and effective for handling different word orders between source and target languages in SMT. However, in terms of hierarchial PB-SMT (HPB), does the syntactic reordering still has a significant impact on its performance? This paper introduces a reordering approach which explores the { (DE) grammatical structure in Chinese. We employ the Stanford DE classifier to recognise the DE structures in both training and test sentences of Chinese, and then perform word reordering to make the Chinese sentences better match the word order of English. The annotated and reordered training data and test data are applied to a re-implemented HPB system and the impact of the DE construction is examined. The experiments are conducted on the NIST 2008 evaluation data and experimental results show that the BLEU and METEOR scores are significantly improved by 1.83/8.91 and 1.17/2.73 absolute/ relative points respectively.
http://doras.dcu.ie/15787/
Marked
Mark
Toward a hybrid integrated translation environment
(2002)
Carl, Michael; Way, Andy; Schaler, Reinhard
Toward a hybrid integrated translation environment
(2002)
Carl, Michael; Way, Andy; Schaler, Reinhard
Abstract:
In this paper we present a model for the future use of Machine Translation (MT) and Computer Assisted Translation. In order to accommodate the future needs in middle value translations, we discuss a number of MT techniques and architectures. We anticipate a hybrid environment that integrates data- and rule-driven approaches where translations will be routed through the available translation options and consumers will receive accurate information on the quality, pricing and time implications of their translation choice.
http://doras.dcu.ie/15827/
Displaying Results 76 - 100 of 259 on page 4 of 11
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