[PDF] Top 20 Findings of the First Shared Task on Machine Translation Robustness
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Findings of the First Shared Task on Machine Translation Robustness
... used translation systems using placeholders in order to create both clean versions of the noisy in-domain datasets, as well as noisy versions of the clean out-of-domain ...back- translation, the JHU team ... See full document
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A Shared Task on Bandit Learning for Machine Translation
... tain rules aimed at improving customer experience on the Amazon retail website (improving read- ability, correction of typos, rewriting of uncom- mon abbreviations, removing irrelevant informa- tion, etc.), naturally the ... See full document
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Robust Machine Translation with Domain Sensitive Pseudo Sources: Baidu OSU WMT19 MT Robustness Shared Task System Report
... Table 4 shows the final results of different meth- ods on test set. Similar with the previous ex- periments, the domain insensitive methods sim- ply mix all the clean, noisy training data. The performance has a little ... See full document
6
Naver Labs Europe’s Systems for the WMT19 Machine Translation Robustness Task
... each translation direction. Our ensemble mod- els ranked first in all language pairs, accord- ing to BLEU ...for robustness to noise and do- main ... See full document
7
Findings of the 2015 Workshop on Statistical Machine Translation
... the first edition of the APE shared task LIMSI submitted two systems (Wisniewski et ...The first one is based on the approach of Simard et ...APE task as a monolingual ... See full document
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Improving Robustness of Neural Machine Translation with Multi task Learning
... Similar findings were outlined in Anastasopoulos et ...for machine translation, Tu et ...the translation de- ...termediate task, should improve the performance of speech ... See full document
7
An Empirical Study of Machine Translation for the Shared Task of WMT18
... balance between different translation preference. The most common solution is to average the pa- rameters of the latest server saved models during the training procedure. We can also combine mod- els with ... See full document
5
Findings of the WMT 2018 Biomedical Translation Shared Task: Evaluation on Medline test sets
... Therefore, biomedicine is a domain for which suitable parallel corpora, official evaluation test sets and machine translation (MT) systems are in high demand. There is active development of par- allel ... See full document
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Findings of the 2010 Joint Workshop on Statistical Machine Translation and Metrics for Machine Translation
... ranking task on Ama- zon’s Mechanical Turk ...ways. First, if we find that it is pos- sible to obtain a sufficient amount of data of good quality, then we might be able to reduce the time commitment ... See full document
37
Deep architectures for Neural Machine Translation
... 2016. Findings of the 2016 Conference on Machine Translation ...the First Conference on Machine Translation, Vol- ume 2: Shared Task ... See full document
9
Findings of the 2009 Workshop on Statistical Machine Translation
... Although the inter-annotator agreement in the sentence-ranking evaluation is only fair (as mea- sured by the Kappa score), agreement can be im- proved by removing the first (up to 50) judgments of each assessor, ... See full document
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Translation Shared Task on Statistical Machine Translation: A Comparison of the Systems Output
... language translation is statistically modeled ...of translation pairs. Unfortunately, even for simple translation models, the search problem is NP ...a robustness in word selection and local ... See full document
7
Neural Monkey: The Current State and Beyond
... (2016). Findings of the 2016 conference on machine translation ...the First Conference on Machine Translation ...2: Shared Task Papers, volume 2, pages 131–198, ... See full document
9
Findings of the Second Shared Task on Multimodal Machine Translation and Multilingual Image Description
... UvA-TiCC (Task 1) The submitted systems are Imagination models (Elliott and K´ad´ar, 2017), which are trained to perform two tasks in a mul- titask learning framework: a) produce the target sentence, and b) ... See full document
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Findings of the Third Shared Task on Multimodal Machine Translation
... of translation studies) to select, from the set of lexical translations lt , only those translations, denoted as clt, which conform to the source context i - both image and its English de- ...the first ... See full document
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Findings of the WMT 2019 Biomedical Translation Shared Task: Evaluation for MEDLINE Abstracts and Biomedical Terminologies
... The first two methods rely on Paragraph Vector (Le and Mikolov, 2014) for sentence representa- tion and scoring formulas based on the cosine sim- ilarity, and the third method focuses on the relative differences ... See full document
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Results from the ML4HMT 12 Shared Task on Applying Machine Learning Techniques to Optimise the Division of Labour in Hybrid Machine Translation
... authors first define a total order on the given translation output which can be used to partition an n-best list of translations into a set of pairwise system ...combine translation output on the ... See full document
6
Machine Translation from an Intercomprehension Perspective
... the first shared task on machine trans- lation between similar languages, we present our first attempts on Czech to Polish machine translation from an intercomprehension ... See full document
5
NTT’s Machine Translation Systems for WMT19 Robustness Task
... improve translation quality for low- resource language pairs and ...We first constructed both of source-to-target and target-to-source trans- lation models with the provided parallel ... See full document
8
Yandex School of Data Analysis Machine Translation Systems for WMT13
... statistical machine translation (SMT) systems developed at Yandex School of Data Analysis for the shared translation task of the ACL 2013 Eighth Workshop on Statistical Machine ... See full document
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