{"title":"面向翻译专业学生的机器翻译在线PYTHON资源库","authors":"Ralph Krüger","doi":"10.51287/cttl_e_2021_2_ralph_kruger.pdf","DOIUrl":null,"url":null,"abstract":"This paper presents an online repository of Python resources aimed at teaching the technical dimension of machine translation to students of translation studies programmes. The Python resources provided in this repository are Jupyter notebooks. These are web-based computational environments in which students can run commented blocks of code in order to perform MT-related tasks such as exploring word embeddings, preparing MT training data, training open-source machine translation systems or calculating automatic MT quality metrics such as BLEU, METEOR, BERTScore or COMET. The notebooks are prepared in such a way that students can interact with them even if they have had little to no prior exposure to the Python programming language. The notebooks are provided as open-source resources under the MIT License and can be used and modified by translator training institutions which intend to make their students familiar with the more technical aspects of modern machine translation technology. Institutions who would like to contribute their own Python-based teaching resources to the repository are welcome to do so. Keywords: translation technology, machine translation, natural language processing, translation didactics, Jupyter notebooks, Python programming","PeriodicalId":40810,"journal":{"name":"Current Trends in Translation Teaching and Learning E","volume":"1 1","pages":""},"PeriodicalIF":0.5000,"publicationDate":"2021-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"AN ONLINE REPOSITORY OF PYTHON RESOURCE FOR TEACHING MACHINE TRANSLATION TO TRANSLATION STUDENTS\",\"authors\":\"Ralph Krüger\",\"doi\":\"10.51287/cttl_e_2021_2_ralph_kruger.pdf\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an online repository of Python resources aimed at teaching the technical dimension of machine translation to students of translation studies programmes. The Python resources provided in this repository are Jupyter notebooks. These are web-based computational environments in which students can run commented blocks of code in order to perform MT-related tasks such as exploring word embeddings, preparing MT training data, training open-source machine translation systems or calculating automatic MT quality metrics such as BLEU, METEOR, BERTScore or COMET. The notebooks are prepared in such a way that students can interact with them even if they have had little to no prior exposure to the Python programming language. The notebooks are provided as open-source resources under the MIT License and can be used and modified by translator training institutions which intend to make their students familiar with the more technical aspects of modern machine translation technology. Institutions who would like to contribute their own Python-based teaching resources to the repository are welcome to do so. Keywords: translation technology, machine translation, natural language processing, translation didactics, Jupyter notebooks, Python programming\",\"PeriodicalId\":40810,\"journal\":{\"name\":\"Current Trends in Translation Teaching and Learning E\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.5000,\"publicationDate\":\"2021-11-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Current Trends in Translation Teaching and Learning E\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.51287/cttl_e_2021_2_ralph_kruger.pdf\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"LINGUISTICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Current Trends in Translation Teaching and Learning E","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.51287/cttl_e_2021_2_ralph_kruger.pdf","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"LINGUISTICS","Score":null,"Total":0}
AN ONLINE REPOSITORY OF PYTHON RESOURCE FOR TEACHING MACHINE TRANSLATION TO TRANSLATION STUDENTS
This paper presents an online repository of Python resources aimed at teaching the technical dimension of machine translation to students of translation studies programmes. The Python resources provided in this repository are Jupyter notebooks. These are web-based computational environments in which students can run commented blocks of code in order to perform MT-related tasks such as exploring word embeddings, preparing MT training data, training open-source machine translation systems or calculating automatic MT quality metrics such as BLEU, METEOR, BERTScore or COMET. The notebooks are prepared in such a way that students can interact with them even if they have had little to no prior exposure to the Python programming language. The notebooks are provided as open-source resources under the MIT License and can be used and modified by translator training institutions which intend to make their students familiar with the more technical aspects of modern machine translation technology. Institutions who would like to contribute their own Python-based teaching resources to the repository are welcome to do so. Keywords: translation technology, machine translation, natural language processing, translation didactics, Jupyter notebooks, Python programming