{"title":"探讨反译对英-爱尔兰语机器翻译的改进","authors":"Meghan Dowling, Teresa Lynn","doi":"10.35903/teanga.v26i0.88","DOIUrl":null,"url":null,"abstract":"In this paper, we discuss the difficulties of building reliable machine translation systems for the English-Irish (EN-GA) language pair. In the context of limited datasets, we report on assessing the use of backtranslation as a method for creating artificial EN-GA data to increase training data for use state-of-the-art data-driven translation systems. We compare our results to earlier work on EN-GA machine translation by Dowling et al (2016, 2017, 2018) showing that while our own systems do not compare in quality with respect to traditionally reported BLEU metrics, we provide a linguistic analysis to suggest that future work with domain specific data may prove more successful.","PeriodicalId":36036,"journal":{"name":"Teanga","volume":"189 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Investigating backtranslation for the improvement of English-Irish machine translation\",\"authors\":\"Meghan Dowling, Teresa Lynn\",\"doi\":\"10.35903/teanga.v26i0.88\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we discuss the difficulties of building reliable machine translation systems for the English-Irish (EN-GA) language pair. In the context of limited datasets, we report on assessing the use of backtranslation as a method for creating artificial EN-GA data to increase training data for use state-of-the-art data-driven translation systems. We compare our results to earlier work on EN-GA machine translation by Dowling et al (2016, 2017, 2018) showing that while our own systems do not compare in quality with respect to traditionally reported BLEU metrics, we provide a linguistic analysis to suggest that future work with domain specific data may prove more successful.\",\"PeriodicalId\":36036,\"journal\":{\"name\":\"Teanga\",\"volume\":\"189 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-11-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Teanga\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.35903/teanga.v26i0.88\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Arts and Humanities\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Teanga","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.35903/teanga.v26i0.88","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Arts and Humanities","Score":null,"Total":0}
Investigating backtranslation for the improvement of English-Irish machine translation
In this paper, we discuss the difficulties of building reliable machine translation systems for the English-Irish (EN-GA) language pair. In the context of limited datasets, we report on assessing the use of backtranslation as a method for creating artificial EN-GA data to increase training data for use state-of-the-art data-driven translation systems. We compare our results to earlier work on EN-GA machine translation by Dowling et al (2016, 2017, 2018) showing that while our own systems do not compare in quality with respect to traditionally reported BLEU metrics, we provide a linguistic analysis to suggest that future work with domain specific data may prove more successful.