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1
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)
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2
Chinese character decomposition for neural MT with multi-word expressions
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)
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3
Wittgenstein in the Machine
Liu, Lydia H.. - 2021
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4
Wittgenstein in the Machine ...
Liu, Lydia H.. - : Columbia University, 2021
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5
Real-time New Zealand sign language translator using convolution neural network
Jayasekera, Mathes Kankanamge Chami. - : The University of Waikato, 2021
Abstract: Over the past quarter of a century, machine Learning performs an essential role in information technology revolution. From predictive internet web browsing to autonomous vehicles; machine learning has become the heart of all intelligence applications in service today. Image classification through gesture recognition is sub field which has benefited immensely from the existence of this machine learning method. In particular, a subset of Machine Learning known as deep learning has exhibited impressive performance in this regard while outperforming other conventional approaches such as image processing. The advanced Deep Learning architectures come with artificial neural networks particularly convolution neural networks (CNN). Deep Learning has dominated the field of computer vision since 2012; however, a general criticism of this deep learning method is its dependence on large datasets. In order to overcome this criticism, research focusing on discovering data- efficient deep learning methods have been carried out. The foremost finding of the data-efficient deep learning function is a transfer learning technique, which is basically carried out with pre-trained networks. In this research, the InceptionV3 pre trained model has been used to perform the transfer learning method in a convolution neural network to implement New Zealand sign language translator in real-time. The focus of this research is to introduce a vision-based application that offers New Zealand sign language translation into text format by recognizing sign gestures to overcome the communication barriers between the deaf community and hearing-unimpaired community in New Zealand. As a byproduct of this research work, a new dataset for New Zealand sign Language alphabet has been created. After training the pre-trained InceptionV3 network with this captured dataset, a prototype for this New Zealand sign language translating system has been created.
Keyword: Artificial intelligence; Computer vision; Convolution Neural Network; Machine learning; Neural networks (Computer science); New Zealand Sign Language -- Translating -- Data processing; Sign language -- Translating -- Data processing; Sign Language Translator; Transfer Learning; Transfer learning (Machine learning); Translating and interpreting -- Data processing
URL: https://hdl.handle.net/10289/14251
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6
AlphaMWE: construction of multilingual parallel corpora with MWE annotations
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)
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7
MultiMWE: building a multi-lingual multi-word expression (MWE) parallel corpora
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) MultiMWE: building a multi-lingual multi-word expression (MWE) parallel corpora. In: 12th International Conference on Language Resources and Evaluation (LREC), 11-16 May, 2020, Marseille, France. (Virtual). (2020)
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8
MT syntactic priming effects on L2 English speakers
In: Resende, Natália orcid:0000-0002-5248-2457 , Cowan, Benjamin orcid:0000-0002-8595-8132 and Way, Andy orcid:0000-0001-5736-5930 (2020) MT syntactic priming effects on L2 English speakers. In: European Association for Machine Translation (EAMT) 2020, 2-6 Nov 2010, Lisbon, Portugal (Online). ISBN 978-989-33-0589-8 (2020)
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9
MultiMWE: building a multi-lingual multi-word expression (MWE) Pparallel corpora
In: Han, Lifeng, Gareth, Jones orcid:0000-0003-2923-8365 and Alan, Smeaton orcid:0000-0003-1028-8389 (2020) MultiMWE: building a multi-lingual multi-word expression (MWE) Pparallel corpora. In: International Conference on Language Resources and Evaluation (LREC), 11-16 May, 2020, Marseille, France. (2020)
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10
Rapid development of competitive translation engines for access to multilingual COVID-19 information
In: Way, Andy orcid:0000-0001-5736-5930 , Haque, Rejwanul orcid:0000-0003-1680-0099 , Xie, Guodong, Gaspari, Federico orcid:0000-0003-3808-8418 , Popović, Maja orcid:0000-0001-8234-8745 and Poncelas, Alberto orcid:0000-0002-5089-1687 (2020) Rapid development of competitive translation engines for access to multilingual COVID-19 information. Informatics . ISSN 2227-9709 (2020)
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11
“A tiny cog in a large machine”: Digital Taylorism in the Translation Industry
In: Moorkens, Joss orcid:0000-0003-0766-0071 (2020) “A tiny cog in a large machine”: Digital Taylorism in the Translation Industry. Translation Spaces, 9 (1). pp. 12-34. ISSN 2211-3711 (2020)
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12
Terminology-aware sentence mining for NMT domain adaptation: ADAPT’s submission to the Adap-MT 2020 English-to-Hindi AI translation shared task
In: Haque, Rejwanul orcid:0000-0003-1680-0099 , Moslem, Yasmin orcid:0000-0003-4595-6877 and Way, Andy orcid:0000-0001-5736-5930 (2020) Terminology-aware sentence mining for NMT domain adaptation: ADAPT’s submission to the Adap-MT 2020 English-to-Hindi AI translation shared task. In: Workshop on Low Resource Domain Adaptation for Indic Machine Translation (Adap-MT 2020), 18-21 Dec 2020, Patna, India (Online). (2020)
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13
An error-based investigation of statistical and neural machine translation performance on Hindi-to-Tamil and English-to-Tamil
In: Ramesh, Akshai, Parthasarathy, Venkatesh Balavadhani, Haque, Rejwanul orcid:0000-0003-1680-0099 and Way, Andy orcid:0000-0001-5736-5930 (2020) An error-based investigation of statistical and neural machine translation performance on Hindi-to-Tamil and English-to-Tamil. In: 7th Workshop on Asian Translation (WAT2020), 4 Dec 2020, Suzhou, China (Online). (2020)
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14
Terminology-aware sentence mining for NMT domain adaptation: ADAPT’s submission to the Adap-MT 2020 English-to-Hindi AI translation shared task
In: Haque, Rejwanul orcid:0000-0003-1680-0099 , Moslem, Yasmin orcid:0000-0003-4595-6877 and Way, Andy orcid:0000-0001-5736-5930 (2020) Terminology-aware sentence mining for NMT domain adaptation: ADAPT’s submission to the Adap-MT 2020 English-to-Hindi AI translation shared task. In: Workshop on Low Resource Domain Adaptation for Indic Machine Translation (Adap-MT 2020), 18-21 Dec 2020, Patna, India (Online). (In Press) (2020)
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15
Identifying complaints from product reviews in low-resource scenarios via neural machine translation
In: Singh, Raghvendra Pratap, Haque, Rejwanul orcid:0000-0003-1680-0099 , Hasanuzzaman, Mohammed orcid:0000-0003-1838-0091 and Way, Andy orcid:0000-0001-5736-5930 (2020) Identifying complaints from product reviews in low-resource scenarios via neural machine translation. In: ICON 2020: 17th International Conference on Natural Language Processing, 18-21 Dec 2020, IIT Patna, India (Online). (2020)
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16
On the integration of linguistic features into statistical and neural machine translation
Vanmassenhove, Eva Odette Jef. - : Dublin City University. School of Computing, 2019. : Dublin City University. ADAPT, 2019
In: Vanmassenhove, Eva Odette Jef orcid:0000-0003-1162-820X (2019) On the integration of linguistic features into statistical and neural machine translation. PhD thesis, Dublin City University. (2019)
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17
Machine translation evaluation resources and methods: a survey
In: Han, Lifeng orcid:0000-0002-3221-2185 (2018) Machine translation evaluation resources and methods: a survey. In: IPRC- Irish Postgraduate Research Conference, 8-9 Nov 2018, Dublin, Ireland. (2018)
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18
Incorporating Chinese radicals into neural machine translation: deeper than character level
In: Han, Lifeng orcid:0000-0002-3221-2185 and Kuang, Shaohui (2018) Incorporating Chinese radicals into neural machine translation: deeper than character level. In: 30th European Summer School in Logic, Language and Information (ESSLLI 2018), 6-17 Aug 2018, Sofia, Bulgaria. (2018)
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19
Incorporating Chinese radicals into neural machine translation: deeper Than character level
In: Han, Lifeng and Kuang, Shaohui (2018) Incorporating Chinese radicals into neural machine translation: deeper Than character level. In: 30th European Summer School in Logic, Language and Information (ESSLLI 2018), 6-17 Aug 2018, Sofia, Bulgaria. (2018)
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20
Apply Chinese radicals Into neural machine translation/ deeper than character level
In: Han, Lifeng orcid:0000-0002-3221-2185 (2018) Apply Chinese radicals Into neural machine translation/ deeper than character level. In: LPRC 2018: Limerick Postgraduate Research Conference, 24 May 2018, Limerick, Ireland. (2018)
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