Systran 6 Greek Language Pack.rarl https://urloso.com/2sMLRp
the quality assessment of machine translation requires the judgment of a human expert, but his/her knowledge is based on two pieces of data that are usually collected using a technique called error analysis, which requires specialized training. the first data is the number of words in the translated text compared to the number of words in the source text. the second data is the number of error messages returned by the machine translation engine. this means that the more different types of errors you find in a document, the better. these errors can be classified based on how they are addressed. in the broadest sense, the categories are: transformation errors occur due to some change in the input, such as an invalid link. then there is an interpretation error. this occurs due to the errors made while machine translation. then, in the case of translation of text in its context there are:the 2019 status of machine translation report states that the average number of symbols translated for every human translator is around 100. it is also stated that the number of symbols translated by mt typically exceeds the number of symbols translated by a single human translator in 8 to 16 times. the thing is, even though mt can produce translations that are closer in length to human translations, it is not even a game changer yet. the focus still lies with the translation of small phrases and the use of text that consists only of simple, directly translatable fragments of text that require no human translation whatsoever.with the increasing use of machine translation and the drop in the market share of human translators, there is a rise in the use of mt by small companies and independent freelancers, plus even by agencies that produce their own content. for one reason, many translation-intensive jobs are the sort of routine, repetitive work that machine translation is perfectly suited for. the downside is, of course, that when the job required the translation of a document of 50 or so pages, or something more substantial, there is a high chance that an agency with little experience in machine translation will be tempted to simply hire someone who speaks the language they need and put the job out to an external translation agency, which in many cases, translates the content only once, even though the content was translated many times. at the same time, freelancers can also use mts for their own work, or as a starting point for translation. an example of the first case is a translator who specializes in technical translations. however, mt doesnt work well in technical writing and this is something we work to make it aware of.
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