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description Publicationkeyboard_double_arrow_right Article 2014 Czech RepublicPublisher:Springer Science and Business Media LLC Publicly fundedFunded by:EC | KHRESMOI, EC | ABU-MATRAN, SFI | CSET CNGL: Next Generatio... +1 projectsEC| KHRESMOI ,EC| ABU-MATRAN ,SFI| CSET CNGL: Next Generation Localisation (CNGL) ,EC| PANACEAPecina, Pavel; Toral, Antonio; Papavassiliou, Vassilis; Prokopidis, Prokopis; Tamchyna, Aleš; Way, Andy; van Genabith, Josef;pmc: PMC4479164
pmid: 26120290
In this paper, we tackle the problem of domain adaptation of statistical machine translation (SMT) by exploiting domain-specific data acquired by domain-focused crawling of text from the World Wide Web. We design and empirically evaluate a procedure for automatic acquisition of monolingual and parallel text and their exploitation for system training, tuning, and testing in a phrase-based SMT framework. We present a strategy for using such resources depending on their availability and quantity supported by results of a large-scale evaluation carried out for the domains of environment and labour legislation, two language pairs (English---French and English---Greek) and in both directions: into and from English. In general, machine translation systems trained and tuned on a general domain perform poorly on specific domains and we show that such systems can be adapted successfully by retuning model parameters using small amounts of parallel in-domain data, and may be further improved by using additional monolingual and parallel training data for adaptation of language and translation models. The average observed improvement in BLEU achieved is substantial at 15.30 points absolute.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2014Full-Text: http://europepmc.org/articles/PMC4479164Data sources: PubMed CentralBiblio at Institute of Formal and Applied LinguisticsArticle . 2015Data sources: Biblio at Institute of Formal and Applied Linguisticsadd 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=10.1007/s10579-014-9282-3&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 12 citations 12 popularity Top 10% influence Top 10% impulse Average Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2014Full-Text: http://europepmc.org/articles/PMC4479164Data sources: PubMed CentralBiblio at Institute of Formal and Applied LinguisticsArticle . 2015Data sources: Biblio at Institute of Formal and Applied Linguisticsadd 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=10.1007/s10579-014-9282-3&type=result"></script>'); --> </script>
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description Publicationkeyboard_double_arrow_right Article 2014 Czech RepublicPublisher:Springer Science and Business Media LLC Publicly fundedFunded by:EC | KHRESMOI, EC | ABU-MATRAN, SFI | CSET CNGL: Next Generatio... +1 projectsEC| KHRESMOI ,EC| ABU-MATRAN ,SFI| CSET CNGL: Next Generation Localisation (CNGL) ,EC| PANACEAPecina, Pavel; Toral, Antonio; Papavassiliou, Vassilis; Prokopidis, Prokopis; Tamchyna, Aleš; Way, Andy; van Genabith, Josef;pmc: PMC4479164
pmid: 26120290
In this paper, we tackle the problem of domain adaptation of statistical machine translation (SMT) by exploiting domain-specific data acquired by domain-focused crawling of text from the World Wide Web. We design and empirically evaluate a procedure for automatic acquisition of monolingual and parallel text and their exploitation for system training, tuning, and testing in a phrase-based SMT framework. We present a strategy for using such resources depending on their availability and quantity supported by results of a large-scale evaluation carried out for the domains of environment and labour legislation, two language pairs (English---French and English---Greek) and in both directions: into and from English. In general, machine translation systems trained and tuned on a general domain perform poorly on specific domains and we show that such systems can be adapted successfully by retuning model parameters using small amounts of parallel in-domain data, and may be further improved by using additional monolingual and parallel training data for adaptation of language and translation models. The average observed improvement in BLEU achieved is substantial at 15.30 points absolute.
Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2014Full-Text: http://europepmc.org/articles/PMC4479164Data sources: PubMed CentralBiblio at Institute of Formal and Applied LinguisticsArticle . 2015Data sources: Biblio at Institute of Formal and Applied Linguisticsadd 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=10.1007/s10579-014-9282-3&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.euAccess RoutesGreen hybrid 12 citations 12 popularity Top 10% influence Top 10% impulse Average Powered by BIP!more_vert Europe PubMed Centra... arrow_drop_down Europe PubMed CentralArticle . 2014Full-Text: http://europepmc.org/articles/PMC4479164Data sources: PubMed CentralBiblio at Institute of Formal and Applied LinguisticsArticle . 2015Data sources: Biblio at Institute of Formal and Applied Linguisticsadd 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=10.1007/s10579-014-9282-3&type=result"></script>'); --> </script>
For further information contact us at helpdesk@openaire.eu