Best Practices

What is Machine Translation Post-Editing or MTPE?

MTPE opens new patterns to translation industry and reflects challenges and opportunities according to our approaches of AI
Rodrigo Demetrio
6 min
Table of Contents

The term Machine Translation Post-Editing, or MTPE, is gaining popularity in the translation market. To understand what MTPE is, let's break down the term?

We've covered some content on Machine Translation here on the blog. It's pretty easy to grasp. Essentially, it's a translation process that involves some kind of engineering, regardless of how sophisticated it is. 

Google, Microsoft, and Amazon Web Services' translation engines are examples. In simple terms, in this type of process, you have an input document and an output document. 

When we add the term “Post-Editing” to the acronym, we're referring to any edits made by a human translator to material that originated from Machine Translation. This includes anything from simple error correction to more refined adjustments.

MTPE: Impacts and Challenges 

MTPE brings productivity benefits. Editing a pre-translated material is more cost-effective than manual translating, word by word. It saves time, money, and facilitates the process.

Efficiency gains are real, but the most notable opportunity of MTPE is operating with Context-Sensitive Translation. This type of translation looks for details, combining machine translation, glossaries, and translation memories. 

Bureau Works CAT Tool Interface Image by Bureau Works

It can offer sophisticated alternatives to the translator about which words to choose in each context and save their choices to improve future suggestions.

However, there are challenges. The precision of MTPE work can vary depending on many factors: language pairs, subject matter, and the quality of training and tuning.

What's the difference between these terms “training and tuning”? Training refers to the input of data volume, while tuning refers to refining that data. These are processes performed by deep learning models, the LLMs.

Even with all this care, machine translation can misinterpret, leading to more work for the translators.

More work or more opportunities for the translator?

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We should say “both!”. You can't escape the work. MTPE requires solid language skills from the translator, as well as technical knowledge to work with machine translation tools and ensure effective editing.

In this process, the translator reviews the text generated by machine translation and makes necessary adjustments to correct errors, improve accuracy, and ensure the final text is clear and coherent in the target language.

Authorship is always a concern when it comes to MTPE. Especially the term “Post-Editing” sparks controversy among linguists. As we always emphasize, the translator's final word is irreplaceable. And it's precisely in these choices that authorship lies. It all depends on how the translator will approach technology to deliver the style required by the client.

In this context, it's fair to say that the demands for translators have increased. Apart from language skills, those who have developed skills to deal with AI are ahead, generating more efficient results, faster responses, and better client satisfaction.

Overall, there's a higher demand for adaptation from the translator and more projects, but from a perspective of more efficient work. Above all, the opportunities lead to better performance results for clients.

Does MTPE apply to any type of translation?

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MTPE may not be the solution for all types of work, but it covers a multitude of thematic areas and project volumes.

It's commonly used in situations where there's a need to translate large volumes of text with tight deadlines, making complete manual translation impractical. It's often employed in sectors like legal, medical, technical, and marketing, where translation accuracy and quality are crucial.

It's also useful when dealing with repetitive or standardized content, such as instruction manuals, contracts, and product catalogs. In these situations, machine translation can be used as an initial tool to generate an approximate translation, which is then refined through Post-Editing to meet the specificities of the target audience.

The truth is, requirements are always changing in any field, and translation is no different. They change precisely because expectations change. 

What do clients in the translation industry demand nowadays? They want brand positioning in global markets, ranking to be found in searches among many others content.

So, in the current landscape, MTPE is one of the strategies that has come to open the way for new workflow patterns in the translation industry, as long as they are applied with criteria.

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Rodrigo Demetrio
Steering the marketing ship at Bureau Works with 17+ years of MarTech under my belt, I transform mere ideas into tangible realities. Passionate about languages and their power to build bridges, let's build a new one?
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