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Transformer-based NMT : modeling, training and implementation
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Xu, Hongfei. - : Saarländische Universitäts- und Landesbibliothek, 2021
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Deep interactive text prediction and quality estimation in translation interfaces
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In: Hokamp, Christopher M. (2018) Deep interactive text prediction and quality estimation in translation interfaces. PhD thesis, Dublin City University. (2018)
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A Hybrid Machine Translation Framework for an Improved Translation Workflow
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Pal, Santanu. - : Saarländische Universitäts- und Landesbibliothek, 2018
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Abstract:
Over the past few decades, due to a continuing surge in the amount of content being translated and ever increasing pressure to deliver high quality and high throughput translation, translation industries are focusing their interest on adopting advanced technologies such as machine translation (MT), and automatic post-editing (APE) in their translation workflows. Despite the progress of the technology, the roles of humans and machines essentially remain intact as MT/APE are moving from the peripheries of the translation field closer towards collaborative human-machine based MT/APE in modern translation workflows. Professional translators increasingly become post-editors correcting raw MT/APE output instead of translating from scratch which in turn increases productivity in terms of translation speed. The last decade has seen substantial growth in research and development activities on improving MT; usually concentrating on selected aspects of workflows starting from training data pre-processing techniques to core MT processes to post-editing methods. To date, however, complete MT workflows are less investigated than the core MT processes. In the research presented in this thesis, we investigate avenues towards achieving improved MT workflows. We study how different MT paradigms can be utilized and integrated to best effect. We also investigate how different upstream and downstream component technologies can be hybridized to achieve overall improved MT. Finally we include an investigation into human-machine collaborative MT by taking humans in the loop. In many of (but not all) the experiments presented in this thesis we focus on data scenarios provided by low resource language settings. ; Aufgrund des stetig ansteigenden Übersetzungsvolumens in den letzten Jahrzehnten und gleichzeitig wachsendem Druck hohe Qualität innerhalb von kürzester Zeit liefern zu müssen sind Übersetzungsdienstleister darauf angewiesen, moderne Technologien wie Maschinelle Übersetzung (MT) und automatisches Post-Editing (APE) in den Übersetzungsworkflow einzubinden. Trotz erheblicher Fortschritte dieser Technologien haben sich die Rollen von Mensch und Maschine kaum verändert. MT/APE ist jedoch nunmehr nicht mehr nur eine Randerscheinung, sondern wird im modernen Übersetzungsworkflow zunehmend in Zusammenarbeit von Mensch und Maschine eingesetzt. Fachübersetzer werden immer mehr zu Post-Editoren und korrigieren den MT/APE-Output, statt wie bisher Übersetzungen komplett neu anzufertigen. So kann die Produktivität bezüglich der Übersetzungsgeschwindigkeit gesteigert werden. Im letzten Jahrzehnt hat sich in den Bereichen Forschung und Entwicklung zur Verbesserung von MT sehr viel getan: Einbindung des vollständigen Übersetzungsworkflows von der Vorbereitung der Trainingsdaten über den eigentlichen MT-Prozess bis hin zu Post-Editing-Methoden. Der vollständige Übersetzungsworkflow wird jedoch aus Datenperspektive weit weniger berücksichtigt als der eigentliche MT-Prozess. In dieser Dissertation werden Wege hin zum idealen oder zumindest verbesserten MT-Workflow untersucht. In den Experimenten wird dabei besondere Aufmertsamfit auf die speziellen Belange von sprachen mit geringen ressourcen gelegt. Es wird untersucht wie unterschiedliche MT-Paradigmen verwendet und optimal integriert werden können. Des Weiteren wird dargestellt wie unterschiedliche vor- und nachgelagerte Technologiekomponenten angepasst werden können, um insgesamt einen besseren MT-Output zu generieren. Abschließend wird gezeigt wie der Mensch in den MT-Workflow intergriert werden kann. Das Ziel dieser Arbeit ist es verschiedene Technologiekomponenten in den MT-Workflow zu integrieren um so einen verbesserten Gesamtworkflow zu schaffen. Hierfür werden hauptsächlich Hybridisierungsansätze verwendet. In dieser Arbeit werden außerdem Möglichkeiten untersucht, Menschen effektiv als Post-Editoren einzubinden.
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Keyword:
ddc:400; ddc:420; ddc:430; ddc:490; ddc:600
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URL: https://doi.org/10.22028/D291-27081
http://nbn-resolving.org/urn:nbn:de:bsz:291-scidok-ds-270811
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Pluricentric languages : automatic identification and linguistic variation ; Plurizentrische Sprachen : automatische Spracherkennung und linguistische Variation
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Statistical post-editing and quality estimation for machine translation systems
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In: Béchara, Hanna (2014) Statistical post-editing and quality estimation for machine translation systems. Master of Science thesis, Dublin City University. (2014)
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Computer assisted (language) learning (CA(L)L) for the inclusive classroom
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Greene, Cara N.. - : Dublin City University. Centre for Next Generation Localisation (CNGL), 2013. : Dublin City University. National Centre for Language Technology (NCLT), 2013. : Dublin City University. School of Computing, 2013
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In: Greene, Cara N. (2013) Computer assisted (language) learning (CA(L)L) for the inclusive classroom. PhD thesis, Dublin City University. (2013)
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Domain adaptation for statistical machine translation of corporate and user-generated content
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In: Banerjee, Pratyush (2013) Domain adaptation for statistical machine translation of corporate and user-generated content. PhD thesis, Dublin City University. (2013)
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Definition of interfaces
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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)
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Mapping the industry I: Findings on translation technologies and quality assessment
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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)
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Quality metrics for human and machine translation.
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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)
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Detecting grammatical errors with treebank-induced, probabilistic parsers
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In: Wagner, Joachim orcid:0000-0002-8290-3849 (2012) Detecting grammatical errors with treebank-induced, probabilistic parsers. PhD thesis, Dublin City University. (2012)
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Deep Syntax in Statistical Machine Translation
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Graham, Yvette. - : Dublin City University. National Centre for Language Technology (NCLT), 2011. : Dublin City University. School of Computing, 2011
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In: Graham, Yvette (2011) Deep Syntax in Statistical Machine Translation. PhD thesis, Dublin City University. (2011)
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Treebank-Based Deep Grammar Acquisition for French Probabilistic Parsing Resources
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Schluter, Natalie. - : Dublin City University. National Centre for Language Technology (NCLT), 2011. : Dublin City University. School of Computing, 2011
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In: Schluter, Natalie (2011) Treebank-Based Deep Grammar Acquisition for French Probabilistic Parsing Resources. PhD thesis, Dublin City University. (2011)
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The integration of machine translation and translation memory
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He, Yifan. - : Dublin City University. Centre for Next Generation Localisation (CNGL), 2011. : Dublin City University. School of Computing, 2011
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In: He, Yifan (2011) The integration of machine translation and translation memory. PhD thesis, Dublin City University. (2011)
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Treebank-based automatic acquisition of wide coverage, deep linguistic resources for Japanese
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Oya, Masanori. - : Dublin City University. National Centre for Language Technology (NCLT), 2010. : Dublin City University. School of Computing, 2010
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In: Oya, Masanori (2010) Treebank-based automatic acquisition of wide coverage, deep linguistic resources for Japanese. Master of Science thesis, Dublin City University. (2010)
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