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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 Page: 1 2 3 4 5...27 Hits 1 – 20 of 526 1 How much context span is enough? Examining context-related issues for document-level MT Castilho, Sheila In: Castilho, Sheila orcid:0000-0002-8416-6555 (2022) How much context span is enough? Examining context-related issues for document-level MT. In: 13th Language Resources and Evaluation Conference, 21-23 June 2022, Marseille, France. (In Press) (2022) BASE Show details 2 An investigation into multi-word expressions in machine translation Han, Lifeng. - : Dublin City University. School of Computing, 2022. : Dublin City University. ADAPT, 2022 In: Han, Lifeng orcid:0000-0002-3221-2185 (2022) An investigation into multi-word expressions in machine translation. PhD thesis, Dublin City University. (2022) BASE Show details 3 An investigation of English-Irish machine translation and associated resources Dowling, Meghan. - : Dublin City University. School of Computing, 2022. : Dublin City University. ADAPT, 2022 In: Dowling, Meghan orcid:0000-0003-1637-4923 (2022) An investigation of English-Irish machine translation and associated resources. PhD thesis, Dublin City University. (2022) BASE Show details 4 The role of machine translation in translation education: A thematic analysis of translator educators’ beliefs Celia Rico; Diana González Pastor In: Translation and Interpreting : the International Journal of Translation and Interpreting Research, Vol 14, Iss 1, Pp 177-197 (2022) (2022) BASE Show details 5 DELA Corpus - A Document-Level Corpus Annotated with Context-Related Issues Castilho, Sheila; Cavalheiro Camargo, João Lucas; Menezes, Miguel... In: Castilho, Sheila orcid:0000-0002-8416-6555 , Cavalheiro Camargo, João Lucas orcid:0000-0003-3746-1225 , Menezes, Miguel and Way, Andy orcid:0000-0001-5736-5930 (2021) DELA Corpus - A Document-Level Corpus Annotated with Context-Related Issues. In: Sixth Conference on Machine Translation (WMT21), 10-11 Nov 2021, Punta Cana, Dominican Republic (Online). ISBN 978-1-954085-94-7 (2021) BASE Show details 6 Can Google Translate Rewire Your L2 English Processing? Way, Andy; Resende, Natália In: Resende, Natália orcid:0000-0002-5248-2457 and Way, Andy orcid:0000-0001-5736-5930 (2021) Can Google Translate Rewire Your L2 English Processing? Digital, 1 (1). pp. 66-85. ISSN 2673-6470 (2021) BASE Show details 7 Chinese character decomposition for neural MT with multi-word expressions Han, Lifeng; Jones, Gareth J.F.; Smeaton, Alan F.... In: Han, Lifeng orcid:0000-0002-3221-2185 , Jones, Gareth J.F. orcid:0000-0003-2923-8365 , Smeaton, Alan F. orcid:0000-0003-1028-8389 and Bolzoni, Paolo (2021) Chinese character decomposition for neural MT with multi-word expressions. In: 23rd Nordic Conference on Computational Linguistics (NoDaLiDa 2021), 31 May- 2 June 2021, Reykjavik, Iceland (Online). (In Press) (2021) BASE Show details 8 Translation quality assessment: a brief survey on manual and automatic methods Smeaton, Alan F.; Jones, Gareth J.F.; Han, Lifeng In: Han, Lifeng orcid:0000-0002-3221-2185 , Jones, Gareth J.F. orcid:0000-0003-2923-8365 and Smeaton, Alan F. orcid:0000-0003-1028-8389 (2021) Translation quality assessment: a brief survey on manual and automatic methods. In: MoTra21: Workshop on Modelling Translation: Translatology in the Digital Age, 31 May- 2 Jun 2021, Rejkjavik, Iceland (Online). (In Press) (2021) BASE Show details 9 Towards document-level human MT evaluation: On the Issues of annotator agreement, effort and misevaluation Castilho, Sheila In: Castilho, Sheila orcid:0000-0002-8416-6555 (2021) Towards document-level human MT evaluation: On the Issues of annotator agreement, effort and misevaluation. In: 16th Conference of the European Chapter of the Association for Computational Linguistics - EACL 2021., 19-23 April 2021, Online. (In Press) (2021) BASE Show details 10 Meta-evaluation of machine translation evaluation methods Han, Lifeng In: Han, Lifeng orcid:0000-0002-3221-2185 (2021) Meta-evaluation of machine translation evaluation methods. In: Workshop on Informetric and Scientometric Research (SIG-MET), 23-24 Oct 2021, Online. (2021) BASE Show details 11 Unsupervised Morphological Segmentation and Part-of-Speech Tagging for Low-Resource Scenarios Eskander, Ramy. - 2021 Abstract: With the high cost of manually labeling data and the increasing interest in low-resource languages, for which human annotators might not be even available, unsupervised approaches have become essential for processing a typologically diverse set of languages, whether high-resource or low-resource. In this work, we propose new fully unsupervised approaches for two tasks in morphology: unsupervised morphological segmentation and unsupervised cross-lingual part-of-speech (POS) tagging, which have been two essential subtasks for several downstream NLP applications, such as machine translation, speech recognition, information extraction and question answering. We propose a new unsupervised morphological-segmentation approach that utilizes Adaptor Grammars (AGs), nonparametric Bayesian models that generalize probabilistic context-free grammars (PCFGs), where a PCFG models word structure in the task of morphological segmentation. We implement the approach as a publicly available morphological-segmentation framework, MorphAGram, that enables unsupervised morphological segmentation through the use of several proposed language-independent grammars. In addition, the framework allows for the use of scholar knowledge, when available, in the form of affixes that can be seeded into the grammars. The framework handles the cases when the scholar-seeded knowledge is either generated from language resources, possibly by someone who does not know the language, as weak linguistic priors, or generated by an expert in the underlying language as strong linguistic priors. Another form of linguistic priors is the design of a grammar that models language-dependent specifications. We also propose a fully unsupervised learning setting that approximates the effect of scholar-seeded knowledge through self-training. Moreover, since there is no single grammar that works best across all languages, we propose an approach that picks a nearly optimal configuration (a learning setting and a grammar) for an unseen language, a language that is not part of the development. Finally, we examine multilingual learning for unsupervised morphological segmentation in low-resource setups. For unsupervised POS tagging, two cross-lingual approaches have been widely adapted: 1) annotation projection, where POS annotations are projected across an aligned parallel text from a source language for which a POS tagger is accessible to the target one prior to training a POS model; and 2) zero-shot model transfer, where a model of a source language is directly applied on texts in the target language. We propose an end-to-end architecture for unsupervised cross-lingual POS tagging via annotation projection in truly low-resource scenarios that do not assume access to parallel corpora that are large in size or represent a specific domain. We integrate and expand the best practices in alignment and projection and design a rich neural architecture that exploits non-contextualized and transformer-based contextualized word embeddings, affix embeddings and word-cluster embeddings. Additionally, since parallel data might be available between the target language and multiple source ones, as in the case of the Bible, we propose different approaches for learning from multiple sources. Finally, we combine our work on unsupervised morphological segmentation and unsupervised cross-lingual POS tagging by conducting unsupervised stem-based cross-lingual POS tagging via annotation projection, which relies on the stem as the core unit of abstraction for alignment and projection, which is beneficial to low-resource morphologically complex languages. We also examine morpheme-based alignment and projection, the use of linguistic priors towards better POS models and the use of segmentation information as learning features in the neural architecture. We conduct comprehensive evaluation and analysis to assess the performance of our approaches of unsupervised morphological segmentation and unsupervised POS tagging and show that they achieve the state-of-the-art performance for the two morphology tasks when evaluated on a large set of languages of different typologies: analytic, fusional, agglutinative and synthetic/polysynthetic. Keyword: Automatic speech recognition--Computer programs; Computer science; Machine translating; Question-answering systems; Speech processing systems--Computer programs URL: https://doi.org/10.7916/d8-jd2d-9p51 BASE Hide details 12 Wittgenstein in the Machine Liu, Lydia H.. - 2021 BASE Show details 13 Wittgenstein in the Machine ... Liu, Lydia H.. - : Columbia University, 2021 BASE Show details 14 Unsupervised Morphological Segmentation and Part-of-Speech Tagging for Low-Resource Scenarios ... Eskander, Ramy. - : Columbia University, 2021 BASE Show details 15 Innovations in machine learning: a case study of the Fabricius Workbench Kelly, Bree. - : Sydney, Australia : Macquarie University, 2021 BASE Show details 16 Meaning and translation : theory and practice of machine translation as exemplified by applicative and cognitive grammars Guerecheau, Chantal. - : University of St Andrews, 2021. : The University of St Andrews, 2021 BASE Show details 17 Machine Translation: Linguistic challenges that arise in the translation of journalistic texts ; Traducción Automática: Retos Lingüisticos que se Presentan en la Traducción de Textos Periodísticos McMahon, Cecilia. - 2021 BASE Show details 18 Real-time New Zealand sign language translator using convolution neural network Jayasekera, Mathes Kankanamge Chami. - : The University of Waikato, 2021 BASE Show details 19 Modelling source- and target-language syntactic Information as conditional context in interactive neural machine translation Gupta, Kamal Kumar; Haque, Rejwanul; Ekbal, Asif... In: Gupta, Kamal Kumar, Haque, Rejwanul orcid:0000-0003-1680-0099 , Ekbal, Asif, Bhattacharyya, Pushpak and Way, Andy orcid:0000-0001-5736-5930 (2020) Modelling source- and target-language syntactic Information as conditional context in interactive neural machine translation. In: Proceedings of the 22nd Annual Conference of the European Association for Machine Translation, 2-6 Nov 2020, Lisboa, Portugal. (2020) BASE Show details 20 AlphaMWE: construction of multilingual parallel corpora with MWE annotations Jones, Gareth J.F.; Smeaton, Alan F.; Han, Lifeng In: Han, Lifeng orcid:0000-0002-3221-2185 , Jones, Gareth J.F. orcid:0000-0003-2923-8365 and Smeaton, Alan F. orcid:0000-0003-1028-8389 (2020) AlphaMWE: construction of multilingual parallel corpora with MWE annotations. In: Joint Workshop on Multiword Expressions and Electronic Lexicons (MWE-LEX 2020), 13 Dec 2020, Barcelona, Spain (Online). (2020) BASE Show details Page: 1 2 3 4 5...27

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