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Machine Translation Post-Editing Types

Machine Translation Post-Editing Types

Post Editing is the next step after completing the machine translation (MT) process and evaluating its output. A human translator processes the document to verify that the source and target texts convey the same information and that the tone of the translation is consistent with the original document. The quality of machine translation varies and affects the subsequent effort required for post editing. There are contributory factors to the quality of the MT such as the clarity and quality of the source text; it is important to make sure that the source text is well-written and well-suited for machine translation beforehand. Other considerable factors that affect MT output quality include: the type of MT used, and the compatibility of the source and target languages. There are two types or levels of post editing Read More »

Evaluation of Machine Translation Output

Evaluation of Machine Translation Output

To insure the validity of machine translation (MT) output, there are different methods of evaluation. A rudimentary form of evaluation is to perform a “round-trip translation”, meaning that the original text is machine translated into the target language, and then the result of that process is translated back into the original language to test the quality of the machine translation. As the quality of machine translation continues to improve, a reliable method for evaluation will also be necessary. Currently, there are two main types of evaluation used for machine translation: human and automated. Read More »

Machine Translation History & Approaches

Machine Translation History & Approaches

Machine Translation (MT) refers to automated language translation. The concept has been around since the 1600’s but has come into its own beginning in the twentieth century. Along with the invention of electronic calculators came the development of ways to adapt computer technology to language translation of documents. Research became prevalent at universities in the mid 1950’s to develop and test machines to perform tasks previously only possible by human translators. Read More »

Machine Translation Post-editing

Machine Translation Post-editing

Solving the Post Edit Puzzle by Paul Filkin (reposted with permission; original post) It would be very arrogant of me to suggest that I have the solution for measuring the effort that goes into post-editing translations, wherever they originated from, but in particular machine translation.  So let’s table that right away because there are many ways to measure, and pay for, post-editing work and I’m not going to suggest a single answer to suit everyone. But I think I can safely say that finding a way to measure, and pay for post-editing translations in a consistent way that provided good visibility into how many changes had been made, and allowed you to build a cost model you could be happy with, is something many companies and translators are still investigating. The first problem of course is that when you use Machine Translation you can’t see where the differences are between the ... Read More »

KantanMT Launches KantanAnalytics™ – Machine Translation Quality Estimation

KantanMT Launches KantanAnalytics™ – Machine Translation Quality Estimation

Segment level quality estimation builds new competitive business models for MT projects KantanMT today announced the release of its breakthrough quality estimation technology, KantanAnalytics™. KantanAnalytics generates quality estimation scores for automated translations generated by a KantanMT engine. These scores will help Project Managers predict the cost and schedule of a Machine Translation project Read More »

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