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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 15 of 15 1 Deep interactive text prediction and quality estimation in translation interfaces Hokamp, Christopher M.. - : Dublin City University. School of Computing, 2018 In: Hokamp, Christopher M. (2018) Deep interactive text prediction and quality estimation in translation interfaces. PhD thesis, Dublin City University. (2018) BASE Show details 2 Statistical post-editing and quality estimation for machine translation systems Béchara, Hanna. - : Dublin City University. School of Computing, 2014 In: Béchara, Hanna (2014) Statistical post-editing and quality estimation for machine translation systems. Master of Science thesis, Dublin City University. (2014) BASE Show details 3 Domain adaptation for statistical machine translation of corporate and user-generated content Banerjee, Pratyush. - : Dublin City University. School of Computing, 2013 In: Banerjee, Pratyush (2013) Domain adaptation for statistical machine translation of corporate and user-generated content. PhD thesis, Dublin City University. (2013) BASE Show details 4 Definition of interfaces Doherty, Stephen; Bicici, Ergun; Toral, Antonio. - : QTLaunchPad, 2013 In: Almaghout, Hala, Bicici, Ergun, Doherty, Stephen orcid:0000-0003-0887-1049 , Gaspari, Federico, Groves, Declan, Toral, Antonio orcid:0000-0003-2357-2960 , van Genabith, Josef orcid:0000-0003-1322-7944 , Popović, Maja orcid:0000-0001-8234-8745 and Piperidis, Stelios (2013) Definition of interfaces. Project Report. QTLaunchPad. (2013) BASE Show details 5 Mapping the industry I: Findings on translation technologies and quality assessment Doherty, Stephen; Gaspari, Federico; Groves, Declan. - : GALA, 2013 In: Doherty, Stephen orcid:0000-0003-0887-1049 , Gaspari, Federico, Groves, Declan and van Genabith, Josef orcid:0000-0003-1322-7944 (2013) Mapping the industry I: Findings on translation technologies and quality assessment. Technical Report. GALA. (2013) BASE Show details 6 Quality metrics for human and machine translation. Doherty, Stephen; van Genabith, Josef; Srivastava, Ankit Kumar. - 2013 In: Doherty, Stephen orcid:0000-0003-4864-5986 , Gaspari, Federico, Groves, Declan, Srivastava, Ankit Kumar and van Genabith, Josef orcid:0000-0003-1322-7944 (2013) Quality metrics for human and machine translation. Project Report. UNSPECIFIED. (2013) BASE Show details 7 Deep Syntax in Statistical Machine Translation Graham, Yvette. - : Dublin City University. National Centre for Language Technology (NCLT), 2011. : Dublin City University. School of Computing, 2011 In: Graham, Yvette (2011) Deep Syntax in Statistical Machine Translation. PhD thesis, Dublin City University. (2011) Abstract: Statistical Machine Translation (SMT) via deep syntactic transfer employs a three-stage architecture, (i) parse source language (SL) input, (ii) transfer SL deep syntactic structure to the target language (TL), and (iii) generate a TL translation. The deep syntactic transfer architecture achieves a high level of language pair independence compared to other Machine Translation (MT) approaches, as translation is carried out at the more language independent deep syntactic representation. TL word order can be generated independently of SL word order and therefore no reordering model between source and target words is required. In addition, words in dependency relations are adjacent in the deep syntactic structure, allowing the extraction of more general transfer rules, compared to other rules/phrases extracted from the surface form corpus, as such words are often distant in surface form strings, as well as allowing the use of a TL deep syntax language model, which models a deeper notion of fluency than a string-based language model and may lead to better lexical choice. The deep syntactic representation also contains words in lemma form with morpho-syntactic information, and this enables new inflections of lemmas not observed in bilingual training data, that are out of coverage for other SMT approaches, to fall within coverage of deep syntactic transfer. In this thesis, we adapt existing methods already successful in Phrase-Based SMT (PB-SMT) to deep syntactic transfer as well as presenting new methods of our own. We present a new definition for consistent deep syntax transfer rules, inspired by the definition for a consistent phrase in PB-SMT, and we extract all rules consistent with the node alignment, as smaller rules provide high coverage of unseen data, while larger rules provide more fluent combinations of TL words. Since large numbers of consistent transfer rules exist per sentence pair, we also provide an efficient method of extracting rules as well as an efficient method of storing them. We also present a deep syntax translation model, as in other SMT approaches, we use a log-linear combination of features functions, and include a translation model computed from relative frequencies of transfer rules, lexical weighting, as well as a deep syntax language model and string-based language model. In addition, we describe methods of carrying out transfer decoding, the search for TL deep syntactic structures, and how we efficiently integrate a deep syntax trigram language model to decoding, as well as methods of translating morpho-syntactic information separately from lemmas, using an adaptation of Factored Models. Finally, we include an experimental evaluation, in which we compare MT output for different configurations of our SMT via deep syntactic transfer system. We investigate various methods of word alignment, methods of translating morpho-syntactic information, limits on transfer rule size, different beam sizes during transfer decoding, generating from different sized lists of TL decoder output structures, as well as deterministic versus non-deterministic generation. We also include an evaluation of the deep syntax language model in isolation to the MT system and compare it to a string-based language model. Finally, we compare the performance and types of translations our system produces with a state-of-the-art phrase-based statistical machine translation system and although the deep syntax system in general currently under-performs, it does achieve state-of-the-art performance for translation of a specific syntactic construction, the compound noun, and for translations within coverage of the TL precision grammar used for generation. We provide the software for transfer rule extraction, as well as the transfer decoder, as open source tools to assist future research. Keyword: Lexical Functional Grammar; Machine translating URL: http://doras.dcu.ie/16078/ BASE Hide details 8 The integration of machine translation and translation memory He, Yifan. - : Dublin City University. Centre for Next Generation Localisation (CNGL), 2011. : Dublin City University. School of Computing, 2011 In: He, Yifan (2011) The integration of machine translation and translation memory. PhD thesis, Dublin City University. (2011) BASE Show details 9 A novel dependency-based evaluation metric for machine translation Owczarzak, Karolina. - : Dublin City University. School of Computing, 2008 In: Owczarzak, Karolina (2008) A novel dependency-based evaluation metric for machine translation. PhD thesis, Dublin City University. (2008) BASE Show details 10 TransBooster:black box optimisation of machine translation systems Mellebeek, Bart. - : Dublin City University. School of Computing, 2007 In: Mellebeek, Bart (2007) TransBooster:black box optimisation of machine translation systems. PhD thesis, Dublin City University. (2007) BASE Show details 11 Automatic extraction of large-scale multilingual lexical resources O'Donovan, Ruth. - : Dublin City University. School of Computing, 2006 In: O'Donovan, Ruth (2006) Automatic extraction of large-scale multilingual lexical resources. PhD thesis, Dublin City University. (2006) BASE Show details 12 Automatic treebank annotation for the acquisition of LFG resources Burke, Michael. - : Dublin City University. School of Computing, 2006 In: Burke, Michael (2006) Automatic treebank annotation for the acquisition of LFG resources. PhD thesis, Dublin City University. (2006) BASE Show details 13 Parsing with automatically acquired, wide-coverage, robust, probabilistic LFG approximations Cahill, Aoife. - : Dublin City University. School of Computing, 2004 In: Cahill, Aoife orcid:0000-0002-3519-7726 (2004) Parsing with automatically acquired, wide-coverage, robust, probabilistic LFG approximations. PhD thesis, Dublin City University. (2004) BASE Show details 14 Treebank annotation with a wide-coverage head-driven phrase structure grammar Schmidtke, Dag. - : Dublin City University. School of Computing, 2004 In: Schmidtke, Dag (2004) Treebank annotation with a wide-coverage head-driven phrase structure grammar. Master of Science thesis, Dublin City University. (2004) BASE Show details 15 A structural alignment model of noun-noun compound interpretation Hayes, Jer. - : Dublin City University. School of Computing, 2003 In: Hayes, Jer (2003) A structural alignment model of noun-noun compound interpretation. Master of Science thesis, Dublin City University. (2003) BASE Show details

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