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1
Machine Translation from Signed to Spoken Languages: State of the Art and Challenges ...
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2
NeuTral Rewriter: A Rule-Based and Neural Approach to Automatic Rewriting into Gender-Neutral Alternatives ...
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3
A Novel Pipeline for Domain Detection and Selecting In-domain Sentences in Machine Translation Systems ...
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4
A Novel Pipeline for Domain Detection and Selecting In-domain Sentences in Machine Translation Systems ...
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5
A Novel Pipeline for Domain Detection and Selecting In-domain Sentences in Machine Translation Systems ...
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6
NeuTral Rewriter: A Rule-Based and Neural Approach to Automatic Rewriting into Gender Neutral Alternatives ...
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7
Machine Translationese: Effects of Algorithmic Bias on Linguistic Complexity in Machine Translation ...
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8
Defining meaningful units. Challenges in sign segmentation and segment-meaning mapping ; 1st International Workshop on Automatic Translation for Signed and Spoken Languages (AT4SSL 2021)
Leeson, Lorraine; De Sisto, Mirella; Shterionov, Dimitar. - : Association for Machine Translation in the Americas, 2021
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9
A review of the state-of-the-art in automatic post-editing [<Journal>]
do Carmo, Félix [Verfasser]; Shterionov, Dimitar [Verfasser]; Moorkens, Joss [Verfasser].
DNB Subject Category Language
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10
Selecting Backtranslated Data from Multiple Sources for Improved Neural Machine Translation
In: Soto, Xabier orcid:0000-0002-3622-6496 , Shterionov, Dimitar orcid:0000-0001-6300-797X , Poncelas, Alberto orcid:0000-0002-5089-1687 and Way, Andy orcid:0000-0001-5736-5930 (2020) Selecting Backtranslated Data from Multiple Sources for Improved Neural Machine Translation. In: Annual Conference of the Association for Computational Linguistics, ACL, 5-10 July 2020, Seattle, WA, USA (Online). (2020)
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11
Selecting Backtranslated Data from Multiple Sources for Improved Neural Machine Translation ...
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12
Towards language-agnostic alignment of product titles and descriptions: a neural approach
In: Stein, Daniel, Shterionov, Dimitar orcid:0000-0001-6300-797X and Way, Andy orcid:0000-0001-5736-5930 (2019) Towards language-agnostic alignment of product titles and descriptions: a neural approach. In: 2019 World Wide Web Conference, 13-17 May 2019, San Francisco, USA. ISBN 978-1-4503-6675-5 (2019)
Abstract: The quality of e-Commerce services largely depends on the accessibility of product content as well as its completeness and correctness. Nowadays, many sellers target cross-country and cross-lingual markets via active or passive cross-border trade, fostering the desire for seamless user experiences. While machine translation (MT) is very helpful for crossing language barriers, automatically matching existing items for sale (e.g. the smartphone in front of me) to the same product (all smartphones of the same brand/type/colour/condition) can be challenging, especially because the seller’s description can often be erroneous or incomplete. This task we refer to as item alignment in multilingual e-commerce catalogues. To facilitate this task, we develop a pipeline of tools for item classification based on cross-lingual text similarity, exploiting recurrent neural networks (RNNs) with and without pre-trained word-embeddings. Furthermore, we combine our language agnostic RNN classifiers with an in-domain MT system to further reduce the linguistic and stylistic differences between the investigated data, aiming to boost our performance. The quality of the methods as well as their training speed is compared on an in-domain data set for English–German products.
Keyword: Machine translating
URL: http://doras.dcu.ie/23867/
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13
APE through neural and statistical MT with augmented data: ADAPT/DCU submission to the WMT 2019 APE Shared task
In: Shterionov, Dimitar orcid:0000-0001-6300-797X , Wagner, Joachim orcid:0000-0002-8290-3849 and do Carmo, Félix orcid:0000-0003-4193-3854 (2019) APE through neural and statistical MT with augmented data: ADAPT/DCU submission to the WMT 2019 APE Shared task. In: Fourth Conference on Machine Translation (WMT19), 01-02 Aug 2019, Florence, Italy. (2019)
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14
Lost in translation: loss and decay of linguistic richness in machine translation
In: Way, Andy orcid:0000-0001-5736-5930 , Shterionov, Dimitar orcid:0000-0001-6300-797X and Vanmassenhove, Eva orcid:0000-0003-1162-820X (2019) Lost in translation: loss and decay of linguistic richness in machine translation. In: MT Summit XVII, 19-23 Aug 2019, Dublin,Ireland. (2019)
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15
Combining SMT and NMT back-translated data for efficient NMT
In: Poncelas, Alberto orcid:0000-0002-5089-1687 , Popović, Maja orcid:0000-0001-8234-8745 , Shterionov, Dimitar orcid:0000-0001-6300-797X , Maillette de Buy Wenniger, Gideon and Way, Andy orcid:0000-0001-5736-5930 (2019) Combining SMT and NMT back-translated data for efficient NMT. In: Recent Advances in Natural Language Processing (RANLP 2019), 2-4 Sept 2019, Varna, Bulgaria. (2019)
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16
ABI Neural Ensemble Model for Gender Prediction Adapt Bar-Ilan Submission for the CLIN29 Shared Task on Gender Prediction ...
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17
Human versus automatic quality evaluation of NMT and PBSMT [<Journal>]
Shterionov, Dimitar [Verfasser]; Superbo, Riccardo [Sonstige]; Nagle, Pat [Sonstige].
DNB Subject Category Language
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18
Integration of a Multilingual Preordering Component into a Commercial SMT Platform
In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 61-72 (2017) (2017)
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19
SignON: Bridging the gap between sign and spoken languages
Saggion, Horacio; Shterionov, Dimitar; Labaka, Gorka. - : CEUR Workshop Proceedings
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