{"title":"Fine-Tuning in Portuguese-English Statistical Machine Translation","authors":"Wilker Aziz, T. Pardo, Ivandré Paraboni","doi":"10.1109/STIL.2009.16","DOIUrl":null,"url":null,"abstract":"In previous work we have shown results of a first experiment in Statistical Machine Translation (SMT) for Brazilian Portuguese and American English using state-of-the-art phrase-based models. In this paper we compare a number of training and decoding parameter choices for fine-tuning the system as an attempt to obtain optimal results for this language pair.","PeriodicalId":265848,"journal":{"name":"2009 Seventh Brazilian Symposium in Information and Human Language Technology","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Seventh Brazilian Symposium in Information and Human Language Technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/STIL.2009.16","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
In previous work we have shown results of a first experiment in Statistical Machine Translation (SMT) for Brazilian Portuguese and American English using state-of-the-art phrase-based models. In this paper we compare a number of training and decoding parameter choices for fine-tuning the system as an attempt to obtain optimal results for this language pair.