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Further Experiments with Shallow Hybrid MT Systems

Authors: nan

Publication: TIPSTER (2010)

DOI: nan

We describe our hybrid machine trans- lation system which has been developed for and used in the WMT10 shared task. We compute translations from a rule- based MT system and …...

28329

Towards Using Web-Crawled Data for Domain Adaptation in Statistical Machine Translation

Authors: nan

Publication: TIPSTER (2011)

DOI: nan

This paper reports on the ongoing work fo- cused on domain adaptation of statistical machine translation using domain-specific data obtained by domain-focused web crawling. We present a strategy for crawl- …...

3293

PROMT DeepHybrid system for WMT12 shared translation task

Authors: nan

Publication: TIPSTER (2012)

DOI: nan

This paper describes the PROMT submission for the WMT12 shared translation task. We participated in two language pairs: English- French and English-Spanish. The translations were made using the PROMT DeepHybrid …...

28123

A discriminative framework of integrating translation memory features into SMT

Authors: nan

Publication: TIPSTER (2014)

DOI: nan

AbstractCombining Translation Memory (TM) with Statistical Machine Translation (SMT) together has been demonstrated to be beneficial. In this paper, we present a discriminative framework which can integrate TM into SMT …...

29075

Rule-based Reordering Space in Statistical Machine Translation

Authors: nan

Publication: TIPSTER (2014)

DOI: nan

AbstractIn Statistical Machine Translation (SMT), the constraints on word reorderings have a great impact on the set of potential translations that are explored. Notwithstanding computationnal issues, the reordering space of …...

15881

RACAI Entry for the IWSLT 2016 Shared Task

Authors: nan

Publication: TIPSTER (2016)

DOI: nan

AbstractSpoken Language Translation is currently a hot topic in the research community. This task is very complex, involving automatic speech recognition, text-normalization and machine translation. We present our speech translation …...

20737

NICT-NAIST System for WMT17 Multimodal Translation Task

Authors: nan

Publication: TIPSTER (2017)

DOI: nan

This paper describes the NICT-NAIST system for the WMT 2017 shared multi- modal machine translation task for both language pairs, English-to-German and English-to-French. We built a hierarchical phrase-based (Hiero) translation …...

27947

Findings of the WMT 2020 Biomedical Translation Shared Task: Basque, Italian and Russian as New Additional Languages

Authors: nan

Publication: TIPSTER (2020)

DOI: nan

AbstractMachine translation of scientific abstracts and terminologies has the potential to support health professionals and biomedical researchers in some of their activities. In the fifth edition of the WMT Biomedical …...

27605

MEDLINE as a Parallel Corpus: a Survey to Gain Insight on French-, Spanish- and Portuguese-speaking Authors’ Abstract Writing Practice

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Publication: TIPSTER (2020)

DOI: nan

AbstractBackground: Parallel corpora are used to train and evaluate machine translation systems. To alleviate the cost of producing parallel resources for evaluation campaigns, existing corpora are leveraged. However, little information …...

14617

UoS Participation in the WMT20 Translation of Biomedical Abstracts

Authors: nan

Publication: TIPSTER (2020)

DOI: nan

AbstractThis paper describes the machine translation systems developed by the University of Sheffield (UoS) team for the biomedical translation shared task of WMT20. Our system is based on a Transformer …...

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Scrambled Translation Problem: A Problem of Denoising UNMT

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Publication: TIPSTER (2021)

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AbstractIn this paper and we identify an interesting kind of error in the output of Unsupervised Neural Machine Translation (UNMT) systems like Undreamt1. We refer to this error type as …...

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Targeted Data Augmentation Improves Context-aware Neural Machine Translation

Authors: nan

Publication: TIPSTER (2023)

DOI: nan

AbstractProgress in document-level Machine Translation is hindered by the lack of parallel training data that include context information. In this work, we evaluate the potential of data augmentation techniques to …...

18314