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Hits 1 – 20 of 42
1
Crossroads semantics : computation, experiment and grammar
Reckman, Hilke
;
Cheng, Lisa L.S.
;
Hijzelendoorn, Maarten
. - Amsterdam : Benjamins, 2017
MPI für Psycholinguistik
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2
An outline of type-theoretical approaches to lexical semantics
Cooper, Robin
;
Retoré, Christian
In: ISSN: 2299-856X ; EISSN: 2299-8470 ; Journal of Language Modelling ; https://hal.archives-ouvertes.fr/hal-01802968 ; Journal of Language Modelling, Institute of Computer Science, Polish Academy of Sciences, Poland, 2017, 5 (2), pp.165-178. ⟨10.15398/jlm.v5i2.200⟩ (2017)
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3
Domain adaptation for statistical machine translation and neural machine translation
Zhang, Jian
. - : Dublin City University. School of Computing, 2017. : Dublin City University. ADAPT, 2017
In: Zhang, Jian orcid:0000-0001-5659-5865 (2017) Domain adaptation for statistical machine translation and neural machine translation. PhD thesis, Dublin City University. (2017)
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4
Detection of verbal multi-word expressions via conditional random fields with syntactic dependency features and semantic re-ranking
Moreau, Erwan
;
Alsulaimani, Ashjan
;
Vogel, Carl
...
In: Maldonado, Alfredo orcid:0000-0001-8426-5249 , Han, Lifeng orcid:0000-0002-3221-2185 , Moreau, Erwan orcid:0000-0001-7692-526X , Alsulaimani, Ashjan, Chowdhury, Koel, Vogel, Carl orcid:0000-0001-8928-8546 and Liu, Qun orcid:0000-0002-7000-1792 (2017) Detection of verbal multi-word expressions via conditional random fields with syntactic dependency features and semantic re-ranking. In: 13th Workshop on Multiword Expressions (MWE 2017), Apr 2017, Valencia, Spain. (2017)
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5
Incorporating visual information into neural machine translation
Calixto, Iacer
. - : Dublin City University. School of Computing, 2017. : Dublin City University. ADAPT, 2017
In: Calixto, Iacer (2017) Incorporating visual information into neural machine translation. PhD thesis, Dublin City University. (2017)
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6
Dublin City University participation in the VTT track at TRECVid 2017
O'Connor, Noel E.
;
Hu, Feiyan
;
Afli, Haithem
...
In: Afli, Haithem orcid:0000-0002-7449-4707 , Hu, Feiyan orcid:0000-0001-7451-6438 , Du, Jinhua orcid:0000-0002-3267-4881 , Cosgrove, Daniel, McGuinness, Kevin orcid:0000-0003-1336-6477 , O'Connor, Noel E. orcid:0000-0002-4033-9135 , Arazo Sánchez, Eric, Zhou, Jiang orcid:0000-0002-3067-8512 and Smeaton, Alan F. orcid:0000-0003-1028-8389 (2017) Dublin City University participation in the VTT track at TRECVid 2017. In: TRECVid workshop, 13-15 Nov 2017, Gaithersburg, Md., USA. (2017)
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7
Machine translation of morphologically rich languages using deep neural networks
Passban, Peyman
. - : Dublin City University. School of Computing, 2017. : Dublin City University. ADAPT, 2017
In: Passban, Peyman (2017) Machine translation of morphologically rich languages using deep neural networks. PhD thesis, Dublin City University. (2017)
Abstract:
This thesis addresses some of the challenges of translating morphologically rich languages (MRLs). Words in MRLs have more complex structures than those in other languages, so that a word can be viewed as a hierarchical structure with several internal subunits. Accordingly, word-based models in which words are treated as atomic units are not suitable for this set of languages. As a commonly used and eff ective solution, morphological decomposition is applied to segment words into atomic and meaning-preserving units, but this raises other types of problems some of which we study here. We mainly use neural networks (NNs) to perform machine translation (MT) in our research and study their diff erent properties. However, our research is not limited to neural models alone as we also consider some of the difficulties of conventional MT methods. First we try to model morphologically complex words (MCWs) and provide better word-level representations. Words are symbolic concepts which are represented numerically in order to be used in NNs. Our first goal is to tackle this problem and find the best representation for MCWs. In the next step we focus on language modeling (LM) and work at the sentence level. We propose new morpheme-segmentation models by which we finetune existing LMs for MRLs. In this part of our research we try to find the most efficient neural language model for MRLs. After providing word- and sentence-level neural information in the first two steps, we try to use such information to enhance the translation quality in the statistical machine translation (SMT) pipeline using several diff erent models. Accordingly, the main goal in this part is to find methods by which deep neural networks (DNNs) can improve SMT. One of the main interests of the thesis is to study neural machine translation (NMT) engines from diff erent perspectives, and finetune them to work with MRLs. In the last step we target this problem and perform end-to-end sequence modeling via NN-based models. NMT engines have recently improved significantly and perform as well as state-of-the-art systems, but still have serious problems with morphologically complex constituents. This shortcoming of NMT is studied in two separate chapters in the thesis, where in one chapter we investigate the impact of diff erent non-linguistic morpheme-segmentation models on the NMT pipeline, and in the other one we benefit from a linguistically motivated morphological analyzer and propose a novel neural architecture particularly for translating from MRLs. Our overall goal for this part of the research is to find the most suitable neural architecture to translate MRLs. We evaluated our models on diff erent MRLs such as Czech, Farsi, German, Russian, and Turkish, and observed significant improvements. The main goal targeted in this research was to incorporate morphological information into MT and define architectures which are able to model the complex nature of MRLs. The results obtained from our experimental studies confirm that we were able to achieve our goal.
Keyword:
Computational linguistics
;
Machine learning
;
Machine translating
URL:
http://doras.dcu.ie/22200/
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8
Entity linking for Tweets
Basile, Pierpaolo
;
Caputo, Annalina
In: Basile, Pierpaolo orcid:0000-0002-0545-1105 and Caputo, Annalina orcid:0000-0002-7144-8545 (2017) Entity linking for Tweets. Encyclopedia with Semantic Computing and Robotic Intelligence, 1 (1). pp. 1-9. ISSN 2529-7376 (2017)
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9
How do users perceive information: analyzing user feedback while annotating textual units
Jones, Gareth J.F.
;
Arora, Piyush
In: Arora, Piyush orcid:0000-0003-0055-345X and Jones, Gareth J.F. orcid:0000-0003-2923-8365 (2017) How do users perceive information: analyzing user feedback while annotating textual units. In: CHIIR 2017 Workshop on Supporting Complex Search Tasks, 11 Mar 2017, Oslo, Norway. (2017)
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10
Perspective Identification in Informal Text
Elfardy, Hebatallah
. - 2017
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11
Painting Pictures with Words - From Theory to System
Coyne, Robert Eric
. - 2017
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12
Evaluative language beyond bags of words: Linguistic insights and computational applications.
Benamara, Farah
;
Taboada, Maite
;
Mathieu, Yannick
In: ISSN: 0891-2017 ; EISSN: 1530-9312 ; Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-02540259 ; Computational Linguistics, Massachusetts Institute of Technology Press (MIT Press), 2017, 43 (1), pp.201-264. ⟨10.1162/COLI_a_00278⟩ (2017)
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13
Synthesizing Sign Language by connecting linguistically structured descriptions to a multi-track animation system
Filhol, Michael
;
McDonald, John
;
Wolfe, Rosalee
In: Lecture Notes in Computer Science ; 11th International Conference on Universal Access in Human-Computer Interaction (UAHCI 2017) held as Part of HCI International 2017 ; https://hal.archives-ouvertes.fr/hal-01849419 ; 11th International Conference on Universal Access in Human-Computer Interaction (UAHCI 2017) held as Part of HCI International 2017, Jul 2017, Vancouver, Canada. ⟨10.1007/978-3-319-58703-5_3⟩ ; http://2017.hci.international/uahci (2017)
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14
Neural architecture for temporal relation extraction: A Bi-LSTM approach for detecting narrative containers
Tourille, J.
;
Ferret, Olivier
;
Tannier, X.
...
In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics ; https://hal-cea.archives-ouvertes.fr/cea-01841667 ; Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, Jul 2017, Vancouver, Canada. pp.224-230, ⟨10.18653/v1/P17-2035⟩ (2017)
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15
El análisis estilométrico aplicado a la literatura española: las novales policiacas e históricas ...
Fradejas Rueda, José Manuel
. - : Humanities Commons, 2017
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16
Annual contributions to the Genealogical World of Phylogenetic Networks II ...
List, Johann-Mattis
. - : Humanities Commons, 2017
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17
A Hybrid Framework for Text Analysis ...
Maisto, Alessandro
. - : Universita' degli studi di Salerno, 2017
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18
Perspective Identification in Informal Text ...
Elfardy, Hebatallah
. - : Columbia University, 2017
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19
Painting Pictures with Words - From Theory to System ...
Coyne, Robert Eric
. - : Columbia University, 2017
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20
Assessing the applicability of surface EMG to tongue gesture detection
Teixeira, António
;
Silva, Samuel
;
Dias, Miguel Sales
. - : Springer International Publishing, 2017
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