The course is packed with information on both machine translation and post-editing practice. It helps you understand the major challenges and advantages of machine translation. And it prepares you to successfully manage machine-translation projects and become confident post-editors.
The course consists of a generic part covering the general skills and practices and two language-specific parts addressing the particular errors by different target languages. The course contains six modules and can be completed in a week (approx. 1 hour per module, the evaluation and the post-editing assignments excluded). Upon successful completion of the course, students obtain the TAUS Post-Editing Certificate and a stamp to add to their e-mail signature and/or web site.
“We are very happy to work together with ProZ.com in promoting this course”, says Jaap van der Meer, director of TAUS.
ProZ.com is hosting the self-paced course on post-editing proposed by TAUS. This course will address the challenges for linguists deciding to work on post-editing assignments.
This online course is aimed at translators and linguists who want to learn the best practices and skills to become more efficient and proficient in the activity of post-editing machine translation output. This material provides comprehensive background information on machine translation, useful details on facts, trends and good general knowledge about post-editing. The practical module contains post-editing of a real machine-translation output. Course modules are in English and the assignments are available in: Arabic, Dutch, Danish, French, Hungarian, Italian, Japanese, Korean, Norwegian, Polish, Spanish, Swedish, Turkish.
Purchase access to the session by using the options below:
The offer includes:
6 Modules | approximately 6 hours (work at your own pace)
2 Assignments | approximately 6 hours
TAUS Post-editing certificate and stamp
Interrupt and resume modules at any time
This course is designed for a wide audience within the language industry, including, but not exclusively for:
Translation students participating in translation training programmes at a university or college
Active translators and editors interested in broadening their skill-set
Teachers and researchers who are involved in translator training and are interested in this new area of the industry
Employees working in different positions at linguistic services providers (project managers, terminologists and language technologists)
Anyone who is interested in translation automation
You will gain the skills necessary to provide high-quality content through post-editing raw MT-output.
The course is packed with information on both machine translation and post-editing practice. It helps you understand the major challenges and advantages of machine translation. And it prepares you to successfully manage machine-translation projects and become confident post-editors. Watch course demo.
The ideal participants for this course are prepared individuals who have:
Some experience in translation and editing
Interest in learning more about machine translation and post-editing
A basic knowledge of translation technology
Perform at native or near-native level and have good translation skills in the selected language
Good translation skills in the selected language and perform at native or near-native level.
Bio: TAUS is a resource center for the global language and translation industries. Our mission is to increase the size and significance of the translation industry to help the world communicate better.
We envision translation as a standard feature, a utility, similar to the internet, electricity and water. Translation available in all languages to all people in the world will push the evolution of human civilization to a much higher level of understanding, education and discovery. We support buyers and providers of language services and technologies with a comprehensive suite of online services, software and knowledge that help them to grow and innovate their business.
We extend the reach and growth of the translation industry through our vision of the Human Language Project and our execution with sharing translation memory data and quality evaluation metrics.
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