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description Publicationkeyboard_double_arrow_right Conference object , Article , Contribution for newspaper or weekly magazine , Other literature type 2018 France, Switzerland, United KingdomPublisher:Association for Computational Linguistics (ACL) Funded by:EC | SUMMA, EC | HimL, EC | TraMOOC +2 projectsEC| SUMMA ,EC| HimL ,EC| TraMOOC ,SNSF| Rich Context in Neural Machine Translation ,SNSF| Dating structural fabric development using high spatial resolution 40Ar/39Ar geochronology: a Combined Filed and Experimental ApproachAuthors: Bawden, Rachel; Sennrich, Rico; Birch, Alexandra; Haddow, Barry;Bawden, Rachel; Sennrich, Rico; Birch, Alexandra; Haddow, Barry;For machine translation to tackle discourse phenomena, models must have access to extra-sentential linguistic context. There has been recent interest in modelling context in neural machine translation (NMT), but models have been principally evaluated with standard automatic metrics, poorly adapted to evaluating discourse phenomena. In this article, we present hand-crafted, discourse test sets, designed to test the models' ability to exploit previous source and target sentences. We investigate the performance of recently proposed multi-encoder NMT models trained on subtitles for English to French. We also explore a novel way of exploiting context from the previous sentence. Despite gains using BLEU, multi-encoder models give limited improvement in the handling of discourse phenomena: 50% accuracy on our coreference test set and 53.5% for coherence/cohesion (compared to a non-contextual baseline of 50%). A simple strategy of decoding the concatenation of the previous and current sentence leads to good performance, and our novel strategy of multi-encoding and decoding of two sentences leads to the best performance (72.5% for coreference and 57% for coherence/cohesion), highlighting the importance of target-side context. Comment: Final version of paper to appear in Proceedings of NAACL 2018
OpenAIRE; Hal-Didero... arrow_drop_down OpenAIRE; Hal-DiderotConference object . 2018Hyper Article en Ligne; Mémoires en Sciences de l'Information et de la CommunicationOther literature type . Conference object . 2018Full-Text: https://hal.science/hal-01800739/documentZurich Open Repository and ArchiveConference object . 2018License: CC BYData sources: Zurich Open Repository and ArchiveEdinburgh Research ExplorerContribution for newspaper or weekly magazine . 2018Data sources: Edinburgh Research ExplorerarXiv.org e-Print ArchiveOther literature type . Preprint . 2017Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2017License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/n18-1118&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 89 citations 89 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!more_vert OpenAIRE; Hal-Didero... arrow_drop_down OpenAIRE; Hal-DiderotConference object . 2018Hyper Article en Ligne; Mémoires en Sciences de l'Information et de la CommunicationOther literature type . Conference object . 2018Full-Text: https://hal.science/hal-01800739/documentZurich Open Repository and ArchiveConference object . 2018License: CC BYData sources: Zurich Open Repository and ArchiveEdinburgh Research ExplorerContribution for newspaper or weekly magazine . 2018Data sources: Edinburgh Research ExplorerarXiv.org e-Print ArchiveOther literature type . Preprint . 2017Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2017License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/n18-1118&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object , Other literature type 2017 United Kingdom, SwitzerlandPublisher:Association for Computational Linguistics (ACL) Funded by:EC | SUMMAEC| SUMMALiepins, R; Germann, U; Barzdins, G; Birch, A; Renals, S; Weber, S; Van Der Kreeft, P; Bourlard, H; Prieto, J; Klejch, O; Bell, P; Lazaridis, A; Mendes, A; Riedel, S; Almeida, MSC; Balage, P; Cohen, S; Dwojak, T; Garner, P; Giefer, A; Junczys-Dowmunt, M; Imran, H; Nogueira, D; Ali, A; Miranda, S; Popescu-Belis, A; Werlen, LM; Papasarantopoulos, N; Obamuyide, A; Jones, C; Dalvi, F; Vlachos, A; Wang, Y; Tong, S; Sennrich, R; Pappas, N; Narayan, S; Damonte, M; Durrani, N; Khurana, S; Abdelali, A; Sajjad, H; Vogel, S; Sheppey, D; Hernon, C; Mitchell, J;We present the first prototype of the SUMMA Platform: an integrated platform for multilingual media monitoring. The platform contains a rich suite of low-level and high-level natural language processing technologies: automatic speech recognition of broadcast media, machine translation, automated tagging and classification of named entities, semantic parsing to detect relationships between entities, and automatic construction / augmentation of factual knowledge bases. Implemented on the Docker platform, it can easily be deployed, customised, and scaled to large volumes of incoming media streams.
UCL Discovery arrow_drop_down Infoscience - EPFL scientific publicationsConference objectData sources: Infoscience - EPFL scientific publicationsadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/e17-3029&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 2 citations 2 popularity Average influence Average impulse Average Powered by BIP!visibility 46visibility views 46 download downloads 49 Powered bymore_vert UCL Discovery arrow_drop_down Infoscience - EPFL scientific publicationsConference objectData sources: Infoscience - EPFL scientific publicationsadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/e17-3029&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object , Preprint , Article , Contribution for newspaper or weekly magazine 2017 United KingdomPublisher:Association for Computational Linguistics (ACL) Funded by:EC | SUMMA, EC | QT21EC| SUMMA ,EC| QT21Authors: Sennrich, Rico;Sennrich, Rico;Analysing translation quality in regards to specific linguistic phenomena has historically been difficult and time-consuming. Neural machine translation has the attractive property that it can produce scores for arbitrary translations, and we propose a novel method to assess how well NMT systems model specific linguistic phenomena such as agreement over long distances, the production of novel words, and the faithful translation of polarity. The core idea is that we measure whether a reference translation is more probable under a NMT model than a contrastive translation which introduces a specific type of error. We present LingEval97, a large-scale data set of 97000 contrastive translation pairs based on the WMT English->German translation task, with errors automatically created with simple rules. We report results for a number of systems, and find that recently introduced character-level NMT systems perform better at transliteration than models with byte-pair encoding (BPE) segmentation, but perform more poorly at morphosyntactic agreement, and translating discontiguous units of meaning. accepted at EACL 2017 (v3: minor fix to table 6 description)
https://www.aclweb.o... arrow_drop_down Edinburgh Research ExplorerContribution for newspaper or weekly magazine . 2017Data sources: Edinburgh Research ExplorerarXiv.org e-Print ArchiveOther literature type . Preprint . 2016Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2016License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/e17-2060&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 12 citations 12 popularity Top 10% influence Average impulse Average Powered by BIP!more_vert https://www.aclweb.o... arrow_drop_down Edinburgh Research ExplorerContribution for newspaper or weekly magazine . 2017Data sources: Edinburgh Research ExplorerarXiv.org e-Print ArchiveOther literature type . Preprint . 2016Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2016License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/e17-2060&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object , Report , Article , Other literature type 2017 SwitzerlandPublisher:Association for Computational Linguistics (ACL) Funded by:EC | SUMMA, SNSF | MODERN: Modeling discours...EC| SUMMA ,SNSF| MODERN: Modeling discourse entities and relations for coherent machine translationAuthors: Pu, Xiao; Mascarell, Laura; Popescu-Belis, Andrei;Pu, Xiao; Mascarell, Laura; Popescu-Belis, Andrei;We propose a method to decide whether two occurrences of the same noun in a source text should be translated consistently, i.e. using the same noun in the target text as well. We train and test classifiers that predict consistent translations based on lexical, syntactic, and semantic features. We first evaluate the accuracy of our classifiers intrinsically, in terms of the accuracy of consistency predictions, over a subset of the UN Corpus. Then, we also evaluate them in combination with phrase-based statistical MT systems for Chinese-to-English and German-to-English. We compare the automatic post-editing of noun translations with the re-ranking of the translation hypotheses based on the classifiers’ output, and also use these methods in combination. This improves over the baseline and closes up to 50% of the gap in BLEU scores between the baseline and an oracle classifier.
https://www.aclweb.o... arrow_drop_down Infoscience - EPFL scientific publicationsReportData sources: Infoscience - EPFL scientific publicationsZurich Open Repository and ArchiveConference object . 2017Data sources: Zurich Open Repository and ArchiveInfoscience - EPFL scientific publicationsConference objectData sources: Infoscience - EPFL scientific publicationsadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/e17-1089&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routeshybrid 3 citations 3 popularity Average influence Average impulse Average Powered by BIP!more_vert https://www.aclweb.o... arrow_drop_down Infoscience - EPFL scientific publicationsReportData sources: Infoscience - EPFL scientific publicationsZurich Open Repository and ArchiveConference object . 2017Data sources: Zurich Open Repository and ArchiveInfoscience - EPFL scientific publicationsConference objectData sources: Infoscience - EPFL scientific publicationsadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/e17-1089&type=result"></script>'); --> </script>
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description Publicationkeyboard_double_arrow_right Conference object , Article , Contribution for newspaper or weekly magazine , Other literature type 2018 France, Switzerland, United KingdomPublisher:Association for Computational Linguistics (ACL) Funded by:EC | SUMMA, EC | HimL, EC | TraMOOC +2 projectsEC| SUMMA ,EC| HimL ,EC| TraMOOC ,SNSF| Rich Context in Neural Machine Translation ,SNSF| Dating structural fabric development using high spatial resolution 40Ar/39Ar geochronology: a Combined Filed and Experimental ApproachAuthors: Bawden, Rachel; Sennrich, Rico; Birch, Alexandra; Haddow, Barry;Bawden, Rachel; Sennrich, Rico; Birch, Alexandra; Haddow, Barry;For machine translation to tackle discourse phenomena, models must have access to extra-sentential linguistic context. There has been recent interest in modelling context in neural machine translation (NMT), but models have been principally evaluated with standard automatic metrics, poorly adapted to evaluating discourse phenomena. In this article, we present hand-crafted, discourse test sets, designed to test the models' ability to exploit previous source and target sentences. We investigate the performance of recently proposed multi-encoder NMT models trained on subtitles for English to French. We also explore a novel way of exploiting context from the previous sentence. Despite gains using BLEU, multi-encoder models give limited improvement in the handling of discourse phenomena: 50% accuracy on our coreference test set and 53.5% for coherence/cohesion (compared to a non-contextual baseline of 50%). A simple strategy of decoding the concatenation of the previous and current sentence leads to good performance, and our novel strategy of multi-encoding and decoding of two sentences leads to the best performance (72.5% for coreference and 57% for coherence/cohesion), highlighting the importance of target-side context. Comment: Final version of paper to appear in Proceedings of NAACL 2018
OpenAIRE; Hal-Didero... arrow_drop_down OpenAIRE; Hal-DiderotConference object . 2018Hyper Article en Ligne; Mémoires en Sciences de l'Information et de la CommunicationOther literature type . Conference object . 2018Full-Text: https://hal.science/hal-01800739/documentZurich Open Repository and ArchiveConference object . 2018License: CC BYData sources: Zurich Open Repository and ArchiveEdinburgh Research ExplorerContribution for newspaper or weekly magazine . 2018Data sources: Edinburgh Research ExplorerarXiv.org e-Print ArchiveOther literature type . Preprint . 2017Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2017License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/n18-1118&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 89 citations 89 popularity Top 1% influence Top 10% impulse Top 1% Powered by BIP!more_vert OpenAIRE; Hal-Didero... arrow_drop_down OpenAIRE; Hal-DiderotConference object . 2018Hyper Article en Ligne; Mémoires en Sciences de l'Information et de la CommunicationOther literature type . Conference object . 2018Full-Text: https://hal.science/hal-01800739/documentZurich Open Repository and ArchiveConference object . 2018License: CC BYData sources: Zurich Open Repository and ArchiveEdinburgh Research ExplorerContribution for newspaper or weekly magazine . 2018Data sources: Edinburgh Research ExplorerarXiv.org e-Print ArchiveOther literature type . Preprint . 2017Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2017License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/n18-1118&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object , Other literature type 2017 United Kingdom, SwitzerlandPublisher:Association for Computational Linguistics (ACL) Funded by:EC | SUMMAEC| SUMMALiepins, R; Germann, U; Barzdins, G; Birch, A; Renals, S; Weber, S; Van Der Kreeft, P; Bourlard, H; Prieto, J; Klejch, O; Bell, P; Lazaridis, A; Mendes, A; Riedel, S; Almeida, MSC; Balage, P; Cohen, S; Dwojak, T; Garner, P; Giefer, A; Junczys-Dowmunt, M; Imran, H; Nogueira, D; Ali, A; Miranda, S; Popescu-Belis, A; Werlen, LM; Papasarantopoulos, N; Obamuyide, A; Jones, C; Dalvi, F; Vlachos, A; Wang, Y; Tong, S; Sennrich, R; Pappas, N; Narayan, S; Damonte, M; Durrani, N; Khurana, S; Abdelali, A; Sajjad, H; Vogel, S; Sheppey, D; Hernon, C; Mitchell, J;We present the first prototype of the SUMMA Platform: an integrated platform for multilingual media monitoring. The platform contains a rich suite of low-level and high-level natural language processing technologies: automatic speech recognition of broadcast media, machine translation, automated tagging and classification of named entities, semantic parsing to detect relationships between entities, and automatic construction / augmentation of factual knowledge bases. Implemented on the Docker platform, it can easily be deployed, customised, and scaled to large volumes of incoming media streams.
UCL Discovery arrow_drop_down Infoscience - EPFL scientific publicationsConference objectData sources: Infoscience - EPFL scientific publicationsadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/e17-3029&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 2 citations 2 popularity Average influence Average impulse Average Powered by BIP!visibility 46visibility views 46 download downloads 49 Powered bymore_vert UCL Discovery arrow_drop_down Infoscience - EPFL scientific publicationsConference objectData sources: Infoscience - EPFL scientific publicationsadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/e17-3029&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object , Preprint , Article , Contribution for newspaper or weekly magazine 2017 United KingdomPublisher:Association for Computational Linguistics (ACL) Funded by:EC | SUMMA, EC | QT21EC| SUMMA ,EC| QT21Authors: Sennrich, Rico;Sennrich, Rico;Analysing translation quality in regards to specific linguistic phenomena has historically been difficult and time-consuming. Neural machine translation has the attractive property that it can produce scores for arbitrary translations, and we propose a novel method to assess how well NMT systems model specific linguistic phenomena such as agreement over long distances, the production of novel words, and the faithful translation of polarity. The core idea is that we measure whether a reference translation is more probable under a NMT model than a contrastive translation which introduces a specific type of error. We present LingEval97, a large-scale data set of 97000 contrastive translation pairs based on the WMT English->German translation task, with errors automatically created with simple rules. We report results for a number of systems, and find that recently introduced character-level NMT systems perform better at transliteration than models with byte-pair encoding (BPE) segmentation, but perform more poorly at morphosyntactic agreement, and translating discontiguous units of meaning. accepted at EACL 2017 (v3: minor fix to table 6 description)
https://www.aclweb.o... arrow_drop_down Edinburgh Research ExplorerContribution for newspaper or weekly magazine . 2017Data sources: Edinburgh Research ExplorerarXiv.org e-Print ArchiveOther literature type . Preprint . 2016Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2016License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/e17-2060&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 12 citations 12 popularity Top 10% influence Average impulse Average Powered by BIP!more_vert https://www.aclweb.o... arrow_drop_down Edinburgh Research ExplorerContribution for newspaper or weekly magazine . 2017Data sources: Edinburgh Research ExplorerarXiv.org e-Print ArchiveOther literature type . Preprint . 2016Data sources: arXiv.org e-Print Archivehttps://doi.org/10.48550/arxiv...Article . 2016License: arXiv Non-Exclusive DistributionData sources: Dataciteadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/e17-2060&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eudescription Publicationkeyboard_double_arrow_right Conference object , Report , Article , Other literature type 2017 SwitzerlandPublisher:Association for Computational Linguistics (ACL) Funded by:EC | SUMMA, SNSF | MODERN: Modeling discours...EC| SUMMA ,SNSF| MODERN: Modeling discourse entities and relations for coherent machine translationAuthors: Pu, Xiao; Mascarell, Laura; Popescu-Belis, Andrei;Pu, Xiao; Mascarell, Laura; Popescu-Belis, Andrei;We propose a method to decide whether two occurrences of the same noun in a source text should be translated consistently, i.e. using the same noun in the target text as well. We train and test classifiers that predict consistent translations based on lexical, syntactic, and semantic features. We first evaluate the accuracy of our classifiers intrinsically, in terms of the accuracy of consistency predictions, over a subset of the UN Corpus. Then, we also evaluate them in combination with phrase-based statistical MT systems for Chinese-to-English and German-to-English. We compare the automatic post-editing of noun translations with the re-ranking of the translation hypotheses based on the classifiers’ output, and also use these methods in combination. This improves over the baseline and closes up to 50% of the gap in BLEU scores between the baseline and an oracle classifier.
https://www.aclweb.o... arrow_drop_down Infoscience - EPFL scientific publicationsReportData sources: Infoscience - EPFL scientific publicationsZurich Open Repository and ArchiveConference object . 2017Data sources: Zurich Open Repository and ArchiveInfoscience - EPFL scientific publicationsConference objectData sources: Infoscience - EPFL scientific publicationsadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/e17-1089&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess Routeshybrid 3 citations 3 popularity Average influence Average impulse Average Powered by BIP!more_vert https://www.aclweb.o... arrow_drop_down Infoscience - EPFL scientific publicationsReportData sources: Infoscience - EPFL scientific publicationsZurich Open Repository and ArchiveConference object . 2017Data sources: Zurich Open Repository and ArchiveInfoscience - EPFL scientific publicationsConference objectData sources: Infoscience - EPFL scientific publicationsadd ClaimPlease grant OpenAIRE to access and update your ORCID works.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.This Research product is the result of merged Research products in OpenAIRE.
You have already added works in your ORCID record related to the merged Research product.All Research productsarrow_drop_down <script type="text/javascript"> <!-- document.write('<div id="oa_widget"></div>'); document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=10.18653/v1/e17-1089&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu