Machine Translation Post-Editing: Best Practices, Workflows, and Tools

Thanks to machine translation, businesses have been able to translate a large number of documents across various languages. Businesses can now produce faster translations in various languages of product descriptions, websites, articles, documents, etc. However, machine translation does not always generate the content that sounds natural or conveys the right meaning.

Machine Translation Post Editing (MTPE) is the process that helps improve the quality of the translated content. MTPE is the combination of machine translation and human review, as it is useful to improve the quality of the translated material. These post-editors do not translate everything from scratch; instead, they review the translation done by the machine and correct the mistakes found according to the purpose of the content.

What Is Machine Translation Post-Editing?

The process of post-editing machine translation involves checking translated content by a machine translation tool for any sort of mistakes. This means that the translated document must be made accurate and understandable by its target audience.

Machine translation systems utilize artificial intelligence and language models in the process. Such tools can process large amounts of content quickly, but they may fail to understand context and select the appropriate words and phrases. Weighing the pros and cons of machine translation helps decide which content is a good fit for post-editing.

At the end of the process, the translator examines the output of the machine translation and makes the required adjustments to it. Depending on the task, this might entail correcting grammar, terms, and sentence structure, as well as checking if the content has retained the meaning of the source text.

Difference Between Post-Editing Machine Translation and Editing Human Translation

The two processes entail the examination of translated materials but incorporate different formats of texts.

Post-editing uses machine-translated text. The post editor checks the machine translation for its correctness, clarity, grammar, and terminology mistakes. Moreover, the amount of post-editing work is determined by the quality of the machine translation and the requirements of the task.

However, editing human translation proceeds from translation performed by a human being. The editor checks the translation for mistakes, consistency, appropriateness, and text readability. In fact, the original translation may reflect the cultural context and the purpose, but it can still have some inaccuracies.

When Should You Use Machine Translation Post-Editing?

MTPE can be a big asset for companies if they need huge volumes of texts translated quickly or don’t have much budget to work with. This method is widely used for product specifications, internal documents, help center articles, and any other content that can benefit from machine translation drafts.

When Not to Use Machine Translation?

Machine translation might not be the best method to use for all projects. Text that deals with legal, medical, financial, and safety information needs to be treated with caution since inaccurate translation can lead to negative consequences. For this kind of content, the benefits of human translation over machine translation usually outweigh the speed advantage.

Light vs Full Post-Editing

MTPE typically employs two tiers of post-editing: light and full. The decision is dependent on how the translated materials will be further used.

Light post-editing aims to ensure the clarity of the content and make the corrections that affect the meaning. Most importantly, it corrects structure and major grammatical mistakes, misleading terminology, and some confusing phrases. Light post-editing does not involve smoothing out the writing style.

Full post-editing consists of a detailed check of the content. The editor verifies correctness, grammar, terminology, readability, tone and consistency. If full post-editing is performed, the result will meet the project quality standards and may concern the public version of the text. A post-translation review checklist helps editors confirm each of these points before the text is published.

Why Machine Translation Post-Editing Matters

MTPE is a useful tool that can make multilingual content management easier for businesses, particularly when the volume of translation is significant. It enables teams to use machine-generated drafts while still involving human review in the translation process.

However, the effectiveness of MTPE depends on the quality of the original translation, as well as the amount of time needed to correct it. In case the text is in dire need of rewriting, all efficiency gains can disappear. A proper workflow helps teams understand when machine translation is beneficial and when human translation is preferred.

Improves Grammatical Accuracy and Spelling Mistakes

Certain things may be automatically translated, but this may create various types of grammar and spelling mistakes, awkward sentences, and unclear messages due to incorrect punctuation. The post-editor reads the text to determine the types of mistakes that cause unclear message and points them out. The editor also checks the grammar and spelling, and if the sentences are grammatically and structurally correct.

Handles Cultural Nuances and Idiomatic Expressions

Not all words have the same meaning in every culture and language. Many things, such as idioms, various expressions, senses of humor, and marketing terms, may lose their meanings when translated literally.

A machine can technically translate a sentence grammatically identical to the original, but may make it unnatural to the local audience. A human post-editor can find more appropriate expressions for the local audience.

MTPE Workflow: How It Works

Pre-Editing and Preparing Source Text

The initiation of the process occurs with the examination of the source text prior to forwarding it for machine translation. Poorly crafted source content is likely to result in a confusing translation; thus, it is essential for the team to correct any vague sentences, spelling issues, and inconsistent terms first. The writer is required to apply direct language and avoid ambiguity in statements. If a sentence has multiple meanings, it is paramount to specify its intended meaning prior to the translation.

Selecting the Machine Translation Engine and Translation Memory

Now comes the selection of a machine translation engine that can support language pair, content type, and other requirements. Different types of systems have different effectiveness depending on the knowledge, the style of the document, etc.

Human Post-Editing

After the process of machine translation is complete, a post-editor takes over the work and analyzes the output against the original document. The editor makes sure that the translation was done correctly, and the converted text does not have any issues when compared with the original one. The review consists of grammar, terminology analysis, and other aspects. AI translation services that combine machine output with human linguists follow this same post-editing step.

Modern MTPE Workflows

Numerous platforms have been created to execute post-editing functions after automated translation yields a translation draft. A translation management system (TMS) is typically included in a workflow. It organizes files and features tasks, monitors the workflow, and combines machine translations with translation memory and quality assurance procedures.

Some workflows include automatic quality control systems that can highlight problematic elements such as terminological inconsistencies, missing data, empty areas, and segments that could not be translated so that editors can detect mistakes, but at the same time do not relieve them from this responsibility.

Tools That Support Machine Translation Post-Editing

Different types of systems support MTPE, and the choice depends on the requirement or type of project.

Machine translation engines provide the initial process of translation, while computer-assisted translation software enables the use of translation memory, terminology databases, etc. A translation management system carries out the project organization and task assignment and controls the other things of the job.

The quality assurance tools help in precise identification of such problems as inconsistent terminology, missing numbers, etc. Localization QA tools like these are especially useful when post-edited content moves into websites or apps. Certain platforms even have simple automated quality estimates that allow teams to decide which segment should be reviewed carefully.

Evaluating MTPE Quality

When assessing the quality of the MTPE, it should be done using specific criteria. Getting an accurate translation may not yield the best result if there are issues such as content changes, incorrect wording, or the wrong audience is reached.

Establishing Quality Standards for Post-Editing

It is crucial to identify what a quality translation consists of before beginning. It is important to know how much editing will be needed, who the target audience will be, and what kind of errors will need correcting. It can also be useful to know if there will be another round of proofreading. Identifying what level of error is present will also help.

Creating a Project-Specific Style Guide

A style guide gives post-editing specialists guidelines about how the text should sound, including informal/formal style, spelling, punctuation, brand voice, formatting, and the way the audience should be addressed.

Common MTPE Challenges

Inconsistent Terminology

In machine-translated texts, the same word could be interpreted differently according to the context. Sometimes this is not a major drawback, but it can lead to confusion for the readers, particularly in technical areas, for instance. Terminology management, with an approved glossary loaded into the workflow, reduces this inconsistency before post-editing begins.

Over-Editing

Editing text generated by machine translation sometimes takes too much time, because post-editors may spend hours rewriting sentences that are already good enough. As a result, the cost and time benefits of machine translation may be lost. The key here is to follow the required level of editing and work only on meaningful improvements. In other words, editors should correct mistakes and improve the text’s readability wherever needed, but they should refrain from rewriting every sentence only because they would say it differently.

Context Errors

A machine can make the wrong word choice due to insufficient context. It can confuse who is talking, which instruction is being referred to, or how one sentence is connected to the other.

The Future of Machine Translation Post-Editing

There have been improvements in machine translation systems, and it is likely that MTPE processes will have a significant change as well. As new tools emerge, machine translation will enable better context, terminology, and integration with translation management systems. In addition, automation will assist teams in detecting common mistakes and identifying crucial content that requires human involvement. This system will make the review process more efficient; however, machines will fail to solve every cultural and legal issue correctly. When comparing machine translation services in the USA, check how each one supports this human review step.

Frequently Asked Questions