{"id":3532,"date":"2024-01-15T13:54:30","date_gmt":"2024-01-15T13:54:30","guid":{"rendered":"https:\/\/poeditor.com\/blog\/?p=3532"},"modified":"2024-01-15T13:54:31","modified_gmt":"2024-01-15T13:54:31","slug":"machine-translation-post-editing","status":"publish","type":"post","link":"https:\/\/poeditor.com\/blog\/machine-translation-post-editing\/","title":{"rendered":"Machine translation post-editing: What you need to know"},"content":{"rendered":"\n
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The art of refining machine-translated text into a masterpiece of linguistic precision involves a human post-editor meticulously reviewing the machine translation (MT) output, meticulously correcting and enhancing it to achieve a level of quality that rivals human-translated content. Meet machine translation post-editing (MTPE).<\/p>\n\n\n\n

In this comprehensive exploration of the subject, we will delve into the process, best practices, benefits, and challenges of post-editing machine translation.<\/p>\n\n\n\n

What is machine translation post-editing?<\/h2>\n\n\n\n

Machine translation post-editing (MTPE) is a process in which human translators review and improve the output generated by machine translation<\/a> systems. The goal of MTPE is to enhance the overall quality and fluency of the translated content, ensuring that it meets the desired level of accuracy and naturalness.<\/p>\n\n\n\n

The process explained<\/h4>\n\n\n\n

Initially, an MT system translates the source text into the target language. This is an automated process where algorithms analyze the input and generate a translation based on predefined patterns and models.<\/p>\n\n\n\n

Following the MT, a human translator (post-editor) reviews and edits the output to correct errors, improve coherence, and enhance the overall quality of the translation. The post-editor compares the machine-generated translation to the source text and makes necessary adjustments to ensure accuracy, fluency, and adherence to specific style or terminology requirements.<\/p>\n\n\n\n

When do you need machine translation?<\/h2>\n\n\n\n

Businesses and translation professionals typically use machine translation when they need to translate a large amount of text quickly. MT can be much faster than human translation, so it is a good option for projects where you have a tight deadline.<\/p>\n\n\n\n

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Utilizing translation machine systems has the potential to reduce translation delivery times by an average of 50%, while also leading to a decrease of 20\u201330% in updates for translations. (Reinke, U. (2013). State of the Art in Translation Memory Technology<\/a><\/em>)<\/p>\n<\/blockquote>\n\n\n\n

MT and MTPE can also reduce the cost of translation. The two are far less expensive than human translation, which is great for businesses with a limited budget. Alas, you may need a translation that is accurate but not necessarily perfect. MTPE can nonetheless improve the accuracy of machine-translated text.<\/p>\n\n\n\n

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According to a survey from Unbabel<\/a>, 39% of responders stated that they incorporate machine translation into their localization strategies. Among these users, 83% express satisfaction with the quality of the generated translations.<\/p>\n<\/blockquote>\n\n\n\n

When not to use machine translation <\/h2>\n\n\n\n

Do not use machine translation when you need a translation that is highly accurate and idiomatic. Machine translation is not as good at capturing the nuances of language as human translation<\/a>, so it may not be the best option for documents that require a high level of precision.<\/p>\n\n\n\n

If you require a translation that is confidential or sensitive, machine translation may not be a good translation option to consider. It can be a security risk, as the machine translation engine may store the source text and use it to train its models. <\/p>\n\n\n\n

Finally, machine translation is not as good at producing creative or persuasive writing as human translation. Marketers may find that it is not the best option for marketing<\/a> materials or other types of creative content.<\/p>\n\n\n

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Challenges of post-editing machine translation<\/h2>\n\n\n\n

Machine translation has come a long way in recent years, but it is still not perfect. There are a number of common mistakes that MT systems make, which can result in inaccurate or unnatural-sounding translations. These include things like:<\/p>\n\n\n\n