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Machine Translation Post-Editing: Perspectives and Best Practices

Read time: 10 min

As artificial intelligence increasingly finds its place in daily affairs, machine translation (MT) continues to improve speed, accuracy, and cost-effectiveness. However, it still has some progress to make before reaching parity with human translators.

That’s where machine translation post-editing (MTPE) comes into play by combining the best of both worlds—the ability of MT engines to quickly handle large volumes of text with the skill and human touch brought by professional linguists.

If you’re looking to harness the power of MTPE in your translation workflows, then this guide is your roadmap to success. Dive in for practical tips and best practices to embrace this effective hybrid translation method and unlock productivity gains.

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What is machine translation post-editing?

It’s only in recent years that machine translation has advanced to a point where it can be used for more than just getting a general idea of the meaning of a text. The rise of neural machine translation (NMT) has seen a significant improvement in accuracy and fluency for many language pairs, but it still falls short of human-level quality for most use cases. This is where machine translation post-editing comes in.

Machine translation post-editing is the process of reviewing and improving machine-translated text to make it more accurate and fluent.

In other words, once the machine translation software generates text in the target language, professional linguists review the output and translation memory matches to ensure the highest possible quality.

Perspectives on machine translation post-editing

With continuous improvements in quality, MTPE is now one of the core advantages of machine translation as a viable alternative to human translation. This has had a direct impact on the translation and localization industry.

From translation buyers to vendors and linguists, everyone involved has had to adapt to this hybrid translation approach—and despite varying levels of adoption, the general agreement is that MTPE is here to stay .

Let’s delve deeper into the various perspectives that influence the adoption of MTPE translation among buyers, vendors, and linguists.

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The buyer perspective on MTPE

Modern businesses have come to see machine translation as a viable productivity tool for entering new markets more quickly while keeping costs low. The advent of neural machine translation has particularly prompted them to leverage their own language data for global growth. Today, the question for most global enterprises is not “if” but “how” they can integrate MT into their localization ecosystem.

Narrowing the perspective down to MTPE, one of the central considerations for large enterprises is how to allocate a budget for MTPE and use it efficiently in the long run.

Although significant for the predictability of MTPE-related costs , cost-effectiveness is mostly not a goal in itself. On the contrary, saving costs on some machine translation projects with MTPE is considered a means of freeing up a budget to support further language pairs or content types for even greater scalability.

All these challenges make the human element of applying MTPE to translation workflows an important factor in the decision-making process.

For example, if a company does not have in-house expertise and resorts to outsourcing, it would usually rely on its existing language service provider (LSP) or engage a new one as a consultant. The LSP would then deliver a proof of concept on all strategic, linguistic, and technological aspects of integrating machine translation and using MTPE.

The vendor perspective on MTPE

The changing demand in the translation and localization market has led many medium to large LSPs to add MT post-editing services to their offerings. This not only makes their portfolio more attractive to buyers and distinguishes them from competitors but also helps them meet their customers’ goals more quickly and consistently provide value.

An experienced post-editor can quickly turn high-quality MT output into a polished translation, but someone who is new to MTPE will need more time—and if the machine translation is sloppy to begin with, even the best post-editor may be unable to salvage it in a reasonable amount of time.

That’s why, if LSPs want to provide value to their customers, they need to have training in place for their linguists to continuously improve their post-editing skills.

The translator perspective on MTPE

Depending on the clients they work with and the types of projects they specialize in, translators may have little to no experience with MTPE. With machine translation being the new normal, many translators are still trying to adopt a clear attitude towards MTPE.

Forward-thinking early adopters have come to trust MT as a productivity tool which they need to be able to adjust to the new demand created on the translation market and complete translation assignments more quickly.

As translators gain experience with MTPE, they develop an understanding of how MT performs on different kinds of texts. This helps them estimate the effort that any given MTPE translation project would require from them.

They also like to have access to a sample of the text that they can use to judge the quality of the MT output. They use this information to determine whether to accept or reject a project.

For example, translators are likely to accept MTPE translation projects involving legal documents, as state-of-the-art MT engines translate them reasonably well. When translators choose to accept a project, they can also use this information to decide what rate to charge.

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The value of pre-editing: Quality source text saves on post-editing

One of the critical initial steps in post-editing machine translation occurs right at the beginning: ensuring you have a tidy input to get a high-quality output.

MT works best with clear and concise input. Put another way— t he better the original MT engine output, the less effort needed during post-editing —resulting in quicker turnaround times and reduced costs.

As early errors can multiply and lead to issues down the line, the source text should be created or pre-edited carefully for both the MT engine and post-editors to have the best material to work with.

That’s why it’s important to ensure that the:

• Original text has as few spelling and grammatical errors as possible
• Terminology and formatting are consistent
• Source text is prepared as if it were intended for a human translator

Let’s go through some practical steps you can take to improve the output.

Strategies for post-editing machine translation output

After the MT engine generates the translation, the level of required post-editing will vary depending on the specific project.

Generally speaking, you can choose between 2 core types of MTPE:

• Light machine translation post-editing
• Full machine translation post-editing

When choosing the right MTPE method for your needs, the 3 primary factors to consider are time, quality, and cost.

Therefore, it’s essential to design your post-editing strategy with these considerations in mind and select the appropriate approach accordingly.

Light post-editing (LPE)

With light post-editing, the initial, raw machine translation output is only modified where absolutely necessary to ensure that the output is legible and accurately conveys the meaning of the source document.

The post-editor should be especially mindful of errors that might hinder the document’s purpose or outright subvert it. Without review, raw MT can create embarrassing results, as one tech giant discovered recently . The editor should aim to make as few edits as possible. This approach can lead to fast and cost-effective results.

Full post-editing (FPE)

With full post-editing, the initial MT output is thoroughly reviewed and modified to ensure that there are no errors whatsoever. Where LPE focuses on the bare essentials of accuracy and legibility, FPE considers a number of factors, including but not limited to:

• Stylistic and tonal consistency within the document (and with other appropriate documents)
• The absence of all grammatical errors
• Appropriate cultural adjustments for the target language (such as idiomatic expressions)

Fully post-edited machine translation should convince the target audience that it was originally created in the target language. This method is slower and more costly than LPE but results in high-quality output.

Which MTPE method to use?

Think of LPE and FPE as being on a spectrum rather than a binary choice. That’s why MTPE requirements should be tailored to the specific translation project.

Set your post-editing priorities based on time, quality, and cost. Prioritizing segments with higher business value (e.g., marketing collateral) can also help.

Another option to consider is bypassing post-editing completely. This can work for projects where the consequences of bad translation are negligible (e.g., internal documentation).

Post-editing tools

Post-editing can be more effective when editors and managers are well-versed in the tools available on the market. Most translation management systems today offer support for post-editing. At Phrase, we believe that MTPE can be a game-changer for companies that seek to connect with international customers, drive engagement, and improve conversion rates.

Here’s an overview of how the Phrase Localization Platform can help you leverage MTPE for your business:

• Set up terminology management systems to help post-editors ensure consistency, including translation memories, term bases, and any useful reference documents. You should always keep these up to date for future projects.
• Use machine translation quality estimation tools, such as Phrase’s Quality Performance Score (QPS) . In Phrase, this AI-powered capability can provide quality scores for all MT output, giving editors an indication of how much MTPE might be required for each specific segment. This can help linguists and project managers decide which segments should be the top priority for post-editing.
• Use translation quality assurance (QA) tools—either integrated or standalone. These will help dynamically identify any issues in the original output that were overlooked or new errors that were introduced during the post-editing step.

Post-editing training and qualifications

Many linguists have learned to rely on machine translation as a productivity tool. They use it to adapt to the new demands in the translation market and to efficiently complete translation assignments.

Still, the post-editor isn’t necessarily a translator. Although there is some overlap in the nature of their work, the exact skills required differ in a few important ways.

In 2017, ISO 18587 defined some key aspects of MTPE, including the specific skills and competencies of the post-editor.

You can expect the best results from qualified and experienced post-editors who have practical experience working in the specified language pairs, with the type of content, and with the relevant tools.

In that direction, it can be helpful to train post-editors for specific tasks before they start on a project.

Post-post-editing

To help improve MTPE results, it’s important to continuously evaluate the process and results using data and feedback. Consider post-editing to be an iterative process that can be improved with time and experience.

A range of tools is available to help with post-editing analysis. For example, an enterprise-grade translation management system, such as Phrase TMS , can help you calculate the post-editing effort, which shows how much work was required by linguists to finalize the translation.

This information can be as granular as required. Knowing, for example, that certain segments require a disproportionate amount of post-editing can help future projects: perhaps the source text can be adjusted, or post-editors can be provided with useful reference documents.

Besides gathering data, it’s invaluable to proactively seek out feedback from all key stakeholders. This can include content creators, post-editors, and project managers. Ask them about their experience with the MTPE project and identify what worked and what can be improved.

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Choose the optimal machine translation engine

There’s a large number of MT engines to choose from and new engines are being developed all the time. Not all engines are created equal, some simply perform better than others. Some are more suitable for specific language pairs or subject matter (domains). Choosing the most effective engine for your project can save a lot of time and effort.

Consider a range of generic MT engines and evaluate them using samples or past experience. Although creating custom analyses can be a time-consuming option, it can lead to cost-effective solutions in the long run.

Another option is to consider a customized translation engine, trained using your own data. This will generally produce high-quality results for the content that you are used to working with.

Phrase offers a unique solution to the problem of choosing the right MT engine . Developed to automatically select the best MT engine for your content, it considers the text’s domain, source and target language, and looks for an optimal MT engine based on past performance. It will always automatically select the best engine for your content.

MTPE has become the new normal

Thanks to continuous quality enhancements, MTPE has evolved into a central asset of machine translation, offering a practical alternative to starting translation from scratch. MTPE lets you blend the speed of machine translation engines in handling large content volumes with the skills of professional linguists, so keep exploring best practices to make the most of it in the long run.

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Our AI Proofreader has been trained on academic texts. It also addresses commonly confused words, and it’s more accurate than Word’s autocorrect feature. Word’s autocorrect feature usually operates on a word level, whereas our AI Proofreader can proofread on the sentence and, to an extent, even the paragraph level. Because it’s more accurate and fixes more than just grammar mistakes, our AI Proofreader identifies and corrects more mistakes overall. Furthermore, because you check your document with our AI Proofreader after you’ve finished writing it, your workflow won’t be interrupted.

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The Ultimate Guide to Machine Translation Post-Editing (MTPE)

Post editing of machine translation is an increasingly important part of translation agencies’ offering. Machine translation is here to stay, which means that machine translation post editing (MTPE) has become an essential service that many businesses rely on. Today, I would like to explore MTPE in detail – what it is, why translators should care about it and how post editors and clients can work together to enhance the overall MTPE process. Shall we dive in?

What is Machine Translation Post-Editing?

Machine translation post-editing (or post editing or postediting, if you prefer) is when a human takes a machine translation (MT) and brings it up to scratch. MT post editing blends the skill and accuracy that the posteditor brings to the task with the speed and convenience of using machine translation. Done well, MTPE can result in high-quality translations that save businesses time and money compared with translations that are carried out in the usual way. I won’t delve too far into the history of machine translation here, other than to note that it has been around as a concept for centuries and as a reality since the 1950s (if you’re interested in translation history more generally, by the way, then check out the link below). In simple terms, machine translation refers to the use of computer software to translate text (either written or spoken) from one language to another. In practice, creating a machine that translates with the nuance and finesse of a human translator has proven tricky. Machine translation quality took a leap forward with the introduction of deep learning and neural networks from around 2014 onwards and it continues to improve today. It delivers impressive time savings, even with the need for MT post editing services factored in. At Tomedes, our skilled posteditors work hard to enhance the quality of machine translations. To do so, they focus on tone, flow, clarity and accuracy, as well as on grammar. They add their nuanced translation expertise to the work that the machine has undertaken. Tomedes’ MT post editors also take account of cultural sensitivities. Based around the globe, our post-editors don’t just deliver linguistic expertise but in-depth local knowledge. This is key to ensuring that translations don’t offend local sensitivities. Appropriate technical knowledge is also a must. Tomedes pairs its MT post editing specialists with work that matches their experience, so that they can apply the right terminology (I’ll explore this in more detail below). It’s all about blending state-of-the-art tech with highly skilled human input – this is the key to successful MTPE. Read more: A Very Brief History of Translation

Why Translators Can Benefit from Embracing MTPE

Machine translation can deliver substantial cost savings to businesses, so many are embracing it as a core part of their translation workflow. This means that translators have a choice between sticking with their traditional methods of translation or adding a new service to their repertoire: post editing of machine translation. When it comes to embracing MTPE, the key benefit for translators is that it opens the door to more work. That includes more work from direct clients and through translation agencies that are looking to recruit post editors. Working with a document that has been produced by a machine, to produce a hybrid translation, is a different kind of work than translating a source document from scratch. It’s ideally suited to those who enjoy editing work as well as translation, as it blends the skills of both roles. Translators who offer MT post editing services display to their clients that they are embracing technology and its benefits and that they are keeping one eye on the future of the language services industry.

How to Get Post Editing of Machine Translation Right – for Businesses

Does your business need to connect with people (whether customers, investors, manufacturers, suppliers or anyone else) on a regular basis in other languages? If so, then it’s likely you’ve been tempted to use machine translation. It’s also likely that you have been disappointed with the results if you did not use a post editor. If you have taken the decision to used post editing machine translation services, then there are steps that you can take to drive up the quality of the resulting translation. These include everything from carefully choosing which machine translation engine and post editor you use, to preparing your document for translation in the right way. I will run through some machine translation post editing best practise tips now, to ensure that you have every chance of success when it comes to your business translations.

Choose Your Machine Translation Engine

Let’s start with how to choose your machine translation engine. This decision can make a major difference to the quality of the translations that you receive. Using a machine translation engine that delivers high quality results can lead to a significant reduction in the amount of time that your post-editor will need to work with your translation. As such, it can be worth looking at premium machine translation engines as well as free software, as the investment can pay off through a reduction in MT post editing hours. The machine translation engine that is right for your business will also depend on which languages you need to translate. Some MT engines deliver better results with European languages, for example, while others specialise in Asian languages. It's a question of finding the right machine translation engine to meet your needs, just as you will need the right post editor. As a general rule of thumb, neural machine translation engines will outperform statistical and rules-based translation engines, though results will vary depending on the content of your translation as well as the languages. DeepL, NMT Systran and Modernmt could all be of interest to you if you are working with languages such as English, French, German, Italian, Portuguese or Spanish. Tencent or Baidu might be a better choice, however, if you’re working with Chinese. Regardless of which languages you need, be sure to research your machine translation options well. The tech side of the languages industry is improving fast, so there may be new entrants into the marketplace that can help you, or more established machine translation tools that have improved their abilities with different languages since I wrote this.

Appoint Your Post-Editor

Just as you put care into choosing the best machine translation engine for your business, the quest to find the perfect MT post editor is also deserving of your time and attention. Several factors come into play here. First, clearly, you will need a translator who has experience of providing machine translation post editing. But that's not all... Your post editor will also need to be a fluent speaker of both your source and target languages – preferably a native speaker of the target tongue. They will also need to have experience of working in your particular sector. Whether you manufacture medical devices, provide financial services or anything else, your translator will need to be familiar with the terminology that people in your industry and in your business frequently use. You have a couple of options open to you here. You can work through a translation agency or seek to engage a posteditor directly. In either case, ensure that the individual who will be providing post editing machine translation services is suitably experienced. And if you plan to use a translation management system, now is the time to discuss that with your potential post editor, to ensure they are experienced/comfortable with it.

Agree Your Machine Translation Post Editing Guidelines

If you have chosen a neural machine translation tool, you should have the option to feed data into it before the translation work begins. This means you can furnish it with glossaries and translation memories that relate to the terminology used in your industry. Doing so should enhance the results of the translation process. Likewise, it is helpful to furnish your post editor with all of the relevant linguistic information prior to them beginning their MT post editing work. Your post editor will also need to know about any elements of the document that you do not want translated: company strap lines, product names or anything else that you want to keep in the original language. A discussion with your post-editor on how any queries should be handled, in addition to the above-mentioned machine translation post editing guidelines, is also useful at this stage, as it can save time once the postedit begins.

Prepare Your Document for Translation

Another way to achieve successful results when using MTPE is to engage in a post of pre-editing. This is where you get your document ready for translation. Key to this is checking it for any errors. After all, the machine will not be able to pick up on them, it only has the chance to compound them and create confusion. The same goes for any content that is ambiguous. It’s also well worth running some sample copy through your machine translation engine. Doing so will give you an idea of the kind of results you can achieve and whether the document you are working with is suited to this type of translation or not. I will expand on the kinds of documents that are not suitable for MTPE in a moment.

Post Postediting Editing

Finally, remember that the process does not end after the post editor finishes their first pass of the document. There will be an element of back and forth required after the MT post editing process takes place. A kind of ‘post postediting editing’ if you will. This final element of the post editing translation process can reasonably be expected to take less time once the machine translation engine and editor are both more familiar with your terminology. However, it is always worth monitoring how long each element of the MTPE process takes, so that that you can assess its efficiency. For more on quality assessment of machine translation, you can click the link below. Read more: How Is Machine Translation Quality Assessed?

Machine Translation Post Editing Guidelines for Translators

Successful post editing of machine translation involves the translator working closely with the client. This relates to many of the points I've included above – terminology, queries and so on – and also to the kind of MTPE service being provided. There is more than one way that post editors can approach this kind of hybrid translation work. Some of the most common MT post editing strategies that translators can use include:

·  Light post-editing – this involves making as few edits as possible while still ensuring the clarity and legibility of the text. It’s a cost-effective approach to MT post editing that delivers speedy results.

·  Full post-editing – as the name suggests, this approach involves a thorough post edit, with the post editor working on everything from style and tone to cultural sensitivities. This will result in a higher quality document than light post-editing, so is ideal for customer-facing documents.

·  Project-specific post-editing – some translation projects will include a range of documents, some of which will require a heavier edit than others. In these instances, it can be helpful to devise a strategy that focuses post editing work appropriately on the documents that need the most attention. Note that the kind of strategy the MT posteditor uses will impact how long the task takes to complete. This has clear implications for the client’s budget and so must be discussed with the client prior to the post editing taking place.

When Not to Use MTPE

Just before I wrap this up, I wanted to add a quick word about when not to use post editing of machine translation. While MTPE is suitable for the majority of translations, if the best practice tips above regarding preparing documents and choosing the right MT engine are followed, it may not be best for more creative types of translation – or rather, for transcreation. Transcreation is a creative type of translation that marketing translators may use when preparing documents for foreign audiences. Doing so can involve creative design work and a great deal of local adaptation, as well as translation. In these instances, it may be better to avoid using machine translation with a post edit and instead opt for using a marketing translation professional to undertake the entire job. As ever, it will depend on the document in question and the company it’s for – I’m just adding this in by way of a final thought.

What are the specific challenges and common errors that post-editors frequently encounter when editing machine-translated content?

Post-editors often deal with issues such as literal translations, lack of cultural nuance, incorrect grammar, and misinterpretation of idioms or colloquial phrases in machine-translated content. Ensuring the translated text reads naturally and conveys the original meaning accurately can be particularly challenging.

How do the costs of MTPE services compare to traditional human translation services?

MTPE services are generally more cost effective than traditional human translation services due to the initial machine translation step, which speeds up the process. However, the exact cost can vary depending on the complexity of the text and the required editing depth.

What are the qualifications or training requirements for becoming a skilled MT post-editor?

Becoming a skilled MT post-editor typically requires a strong background in both the source and target languages, familiarity with the subject matter, and an understanding of translation technology. Formal training or certification in translation and editing can also be beneficial.

MTPE can save businesses a great deal of time and money but it’s important to get it right. Hopefully the advice above should help with that. And if you’re inspired to learn more about machine translation and its role in helping businesses connect with the world, why not check out my thoughts on the top machine translation trends for 2024?

By Ofer Tirosh

Ofer Tirosh is the founder and CEO of Tomedes, a language technology and translation company that supports business growth through a range of innovative localization strategies. He has been helping companies reach their global goals since 2007.

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Machine Translation for assignments

Use of machine translation, using machine translation in your assignment, risks with using machine translation, citing machine translation.

Machine Translation is an automated process in which a computer program converts text in one language into another.

You are:

• using Machine Translation if you write your assessment in one language and automatically convert it to English through a computer program or internet application.
• not using Machine Translation if you write your assessment in English and use a writing tool (e.g. Microsoft Editor or Grammarly) to check your grammar and offer suggestions for better phrasing.

Some Machine Translation tools utilise generative artificial intelligence. Visit using AI tools in your studies  to find out what you need to consider before using these tools. Our Generative AI tools for assignments  referencing guide has tips on how to cite or acknowledge your use of these tools.

UQ graduates should be able to independently demonstrate a high standard of written and verbal communication skills. Using language fluently and without assistance is crucial in the workplace.

Some assessments do not permit the use of Machine Translation, while others may allow it with some limitations.

• Course Profile
• Learn.UQ (Blackboard) course site

You can also ask your Course Coordinator if you are unsure.

Once you submit an assessment item, you are responsible for all work produced by Machine Translation, including errors that arise.

Any permitted use of Machine Translation for assessment must be acknowledged appropriately .

Your Course Coordinator will provide guidance on how to reference the use of AI tools .

Examples of how to reference your use of Machine Translation include:

• citing or referencing in the text or list of references
• inclusion in your methodology.
• Verify the accuracy of the product you use. Machine Translation does not always produce an exact or accurate translation.
• Do not supply sensitive information , including personal, confidential or proprietary information or data to Machine Translation tools.

You must acknowledge that you have used Machine Translation in your assessment. Failure to acknowledge the use of Machine Translation can result in Academic Misconduct .

Acknowledgement

Acknowledgement should include the extent to which you used Machine Translation. For example, you might acknowledge:

• specific sections of work submitted
• a specific action in a document such as editing, correcting or translating
• ‘post-editing’ which means that the entire document has been translated by Machine Translation and then corrected and adjusted by you.

Examples of how you might acknowledge use

For a specific section : Chapter 5 was produced with the assistance of <insert tool name> (eg. Google Translate, BabelFish, Grammarly, ChatGPT etc). The text was originally written in its entirety in English.

For a specific action for the whole document: The work was edited/corrected/translated using <insert tool>.

For your input after Machine Translation: This article was translated into English from [LANGUAGE] using <insert tool>. The author is unable to verify accuracy/the author used <insert tool> to verify the translation provided.

For your input after Machine Translation: This work was post-edited by the author, after being translated from <insert language> to English using <insert tool>.

For your input after Machine Translation: Interview transcripts in Indonesian were translated into English using <insert tool>. The author then checked the results for accuracy.

Referencing

Not all referencing styles provide guidance on how to reference machine translation. Many Machine Translation tools use AI. Visit generative AI tools for assignments for tips on how to cite or acknowledge your use of these tools.

References should:

• provide clear and accurate information for the tool
• identify where Machine Translation has been used in your work.

You can acknowledge your use of Machine Translation by:

• including a page at the front of your assessment to give these details
• putting a note in the reference list
• using a footnote or end note.

If in doubt, check with your course coordinator or ask the Library.

• Last Updated: Aug 7, 2024 8:32 AM
• URL: https://guides.library.uq.edu.au/referencing/machine-translation

An Insider’s Guide to the Role of an Editor

• February 18, 2020

Accuracy is a vital pillar for our business. At Terra, we achieve the highest accuracy on projects through a critical review process and workflow that includes the role of the Editor. The Editor is imperative in achieving quality deliverables. After the translator has finished their assignment, editing is the next step in the process. Editors are first to revise the translation and the second team member to work with the source text. They compare the target language content against the original to ensure meaning and context are not lost. In addition to this key responsibility, editors must also review and answer queries from translators and Quality Assurance Managers (QAM) , evaluate and score quality, and provide constructive feedback to the translator.

A Typical Day in the Role of an Editor

A day likely begins with the Editor checking on new assignments or urgent queries that need to be answered. This typically dictates the pace for the rest of the workday. After deadlines and priorities are sorted, the Editor will dive into an edition. When an edition is completed, the Editor will pass along the project to the next team member in the workflow, the QAM. At Terra, no two days are the same in the role of an Editor. Projects vary in length, difficulty and subject matter because each project requires a different set of linguistic and communication skills.

Why is the Editor Important?

The Editor’s role is valuable because he or she improves the overall quality of the translation with a focus on vocabulary, grammar, semantics, style and punctuation. They review the entire translation comparing it to the source to ensure the original content is rendered accurately in the target language. The Editor also makes certain the target text reads naturally and fluently as if it were not a translation. When large projects are split among multiple translators, the Editor is responsible for keeping consistency across the project that includes terminology and style. Additionally, the Editor certifies that the work complies with the client’s requirements and guidelines.

“The value added to the translation process by the Editor is accuracy, consistency, coherence, compliance and quality,” explained Alejandro Kochol, Editor for Terra. “The translation is polished and the quality of the deliverable is enhanced by the Editor.”

An Editor’s Core Skills

The top skills of an experienced Editor include dynamic linguistic prowess, source and target language knowledge, cultural and subject knowledge, attention to detail, flexibility, adaptability, ability to research and multitask, advanced knowledge of computer and CAT tool software , and excellent communication. 

Discernment is another crucial skill for the Editor. A large component of an Editor’s role is the ability to leave out personal preferences. The Editor should avoid imposing their own style and over-correct the translation. This can pose a challenge because it’s tempting to make changes due to personal choices. If the style used by the translator is appropriate in every aspect, the Editor should recognize this and respect it. 

Common Misconceptions of the Editor

A common misconception is that editing and proofreading are the same tasks. This is not the case. Editing involves improving a translation by comparing the source and target text. Proofreading involves revising the translation alone. The source text is used only as a reference if it is absolutely necessary.

A Love for Language

Most editors have a true passion for linguistics. They also appreciate that every day brings a new set of challenges and they find joy in creating solutions. There is a great power in words and a proficient Editor is meticulous in the use of every word in order to improve the quality of the translation. 

“I love working with texts and languages,” said Alejandro. “I enjoy meticulously examining every part of the translation to adjust errors and ensure nothing is missing. Being an Editor allows me to use my talents to improve the entire translation process.”

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Help improve intercultural connections through translations

Fairlingo is a unique translation platform where a translator and revisor work together on a translation in the cloud. You get valuable feedback from other translators and become a better translator. Fairlingo is suitable for both starting translators and professional translators.

What do we offer translators?

Flexibility, translate together, smart technology, what we offer you, post-editing.

per revised word: €0.015

With our post-editing assignments, the text is machine-translated first. As a translator, you only have to revise the translation. The rate is € 0.015 per revised word, and you will be paid through PayPal.

per translated word €0.03 per revised word: €0.01

You are a (starting) translator and the target language is your mother tongue. We offer you € 0.03 per translated word and € 0.01 per revised word. You will be paid through PayPal.

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per translated word: €0.06 per revised word: €0.011

With demonstrable professional translation experience, you can start at this level. You will earn € 0.06 per translated word and € 0.011 per revised word. You will be paid through PayPal.

Sworn translations For sworn translations you will earn € 45 per translated page plus € 8.80 registered mail compensation per translation. For more information, please visit this page.

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We regularly have texts that need to be translated or revised, either for ourselves or for our own clients. Fairlingo is quick, simple and affordable! In other words, a perfect solution.

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Most translators I know also work as editors. There seems to be an industry assumption that translators do both by default. This makes sense, of course: the translator-turned-editor knows the source and target languages and is also an excellent reader and writer. However, revising one’s own work is different from revising someone else’s. And without training or clear expectations for the role, editors might misunderstand their task to be aligning the translation to what they would have done as translators. Competitiveness may even come into play; an editing task can seem like a chance to prove you’re a better translator by catching all the errors. Unfortunately, this mindset damages the translator-editor relationship and prevents healthy collaboration.

Since 2016, I have had the privilege of working with a translator collective, in which the members translate and edit each other’s work. This structure has allowed me to improve my own editing process over time and think more about the editor’s role in the translation industry. Transparency in editing has also challenged me to move past the “gotcha” mindset and start viewing the process as a collaboration. Effective collaborations result in better quality, which is something language professionals are always striving for.

So, throw on your editor’s hat. Whether you have an established transparent translator-editor partnership or you are editing translations by an anonymous person or someone you’ve never worked with before, here are some tips and reminders for nurturing that partnership:

Be a team player.

With every edit you make and every comment you leave, remember that your job as an editor is to improve the text. You are working with the translator to create a text fit for the client’s purposes.

If you frame yourself in an adversarial role, as someone who is just fixing what the translator did incorrectly, you might let that negative tone inform your communication with the translator. Understand that you and the translator have the same goal.

Clarify the brief.

Some clients only want you to correct objective errors and may give you a chart. Other clients want the text to sound like it was written in the target language. It’s important to clarify with the client, especially if it’s a first-time client, what kind of editing is needed. Clients have different quality expectations for different text types. Typically, if a translator receives an editing task, they are being asked to do the following:

• Revise: Compare the source and the target and evaluate the accuracy of the translation.
• Copyedit: Make sure the translated document (target document) adheres to a particular style and check spelling, punctuation, grammar, and usage.

There are other types of editing, like structural editing and content editing, but clients should be explicit if those types are expected. Also keep in mind that terms like editing and proofreading are used differently outside of the translation world. In publishing, proofreading is checking the document after it’s already in its final format. Some language service providers might ask for a proofread and be referring to a light copyedit for mechanical errors.

Justify your changes.

For the revision aspect of an editor’s role, remember there is often more than one way to translate a word or concept. Ask yourself, is this really an error? Or is this a preferential change? Take a look at the error categories for the ATA certification exam (or a chart that the client has provided) so you can point to a specific reason if asked.

When copyediting, if you find yourself making changes because “it sounds better like this,” consider some additional copyediting training and read up on principles of grammar and style. It’s also important to familiarize yourself with some style manuals. Chicago Manual of Style is my personal favorite, and I also use the American Medical Association Manual of Style for some clients. Some clients also have in-house style guides or preferred date and time formats, so make sure to ask the client before you start editing. Professional associations such as ACES: The Society for Editing are also great resources for editors.

Don’t be a snob.

This is a reminder I tell myself all the time. I’m constantly trying to unlearn the prescriptivist tendencies of my high school days when I would gleefully correct people’s grammar to feel that thrill of superiority. I know it’s part of your job as a translation editor to align the text to spelling and grammar conventions, but it’s not helpful to come across as a know-it-all or make a sentence sound awkward because you refuse to end a sentence with a preposition or use the “singular they.” Depending on the text type, the goal is often clarity and readability. Keep that end in mind, and be gentle and helpful if you must be pedantic.

Focus on feedback.

Many translators want to receive feedback on their translations. Constructive feedback enables translators to improve their craft.

Put your translator hat back on for a second. The initial gut-response to feedback for many translators is defensiveness, with good reason: we have often spent many hours (days! months!) on certain choices, so it’s difficult to accept that there may be room for improvement. Try to push through that emotion and recognize, again, that editors and translators have the same goal: to improve the text. Also remember that you’re allowed to disagree with your editor. You may have a very specific reason for your translation choice. Learn to tell the difference between feeling possessive and being confident.

Editors, back to you. Here are some tips to keep in mind when leaving feedback.

• Positive feedback is nice to hear! Did you think the translator had a particularly clever way of rendering the translation? Are you impressed that they worked cattywampus into a text? Tell them so!
• Limit your comments to the work itself. Do not venture into the territory of calling someone a bad translator. Maybe the translator is a newbie, in which case your edits may be very helpful and constructive to them. Or maybe the translator is having a bad week. I think we can all relate to the struggle of producing quality work in the midst of difficult times. Assume that all comments will get back to the translator.
• Review your comments before final delivery. If you’re feeling particularly cranky after changing the same error type for the umpteenth time, it’s possible you let your mood affect your tone along the way. After you finish editing, take a break! Come back after a break and read through the comments before delivery. Keep your comments clear and professional.

I’ll never forget one of my first translation assignments for a translation agency. I translated a text for which I was out of my depth, using all the wrong terminology and register. The marked-up text I received back from the editor was…comprehensive. I doubt any of my original translation was left untouched. But I distinctly remember that the comments were polite, straightforward, and helpful. The editor included a couple resources and advised me on accepted terminology in the field. They may have been fuming. They may have shaken their fist at the screen and questioned why I was allowed to be working on this text type. But whatever their personal feelings about my translation, they improved the text, and they came across as helpful and professional. I strive to do the same. I hope you will, too.

ACES: The Society for Editing: https://aceseditors.org/

ATA Explanation of Error Categories: https://www.atanet.org/certification/how-the-exam-is-graded/error-categories/

Brian Mossop. Revising and editing for translators (London: Routledge, 2020).

This blog post was edited by Emily Moorlach of The Savvy Newcomer team

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Assignment Editor

Job description.

• Tracks stories from all sources including government agencies, wire services and community groups
• Dispatches photographers, reporters and other personnel to cover stories
• Coordinates logistics for news personnel
• Participates in daily story meetings and supplies a comprehensive list of all possible news stories and works with the News Director to develop plans for all broadcasts
• Assists in development, planning and follow-up of all news stories
• Edits video clips as assigned
• Writes stories for the web and other eMedia platforms
• Interacts with viewers/users on social media sites
• Performs other duties as assigned
• Bachelor's degree in Journalism, or a related field, or an equivalent combination of education and work-related experience
• Fluency in English
• Excellent communication skills, both oral and written
• Minimum two years’ experience in news operations
• Proficiency with computers, telephones, copiers, scanners, fax machines and other office equipment
• Ability to meet deadlines, prioritize assignments and handle multiple tasks simultaneously
• Flexibility to work any shift
• Attention to detail.
• Passion for local news, curiousity, adaptability, and works well with others.

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▾ Dictionary English-French

Assignment noun ( plural: assignments ) —, mission f ( plural: missions f ), attribution f, assign ( sb./sth. ) verb ( assigned , assigned ) —, attribuer v, affecter (qqn.) v, assigner qqch./qqn. v, nommer qqn. v, allouer qqch. v, mandater qqch./qqn. v, assign sb./sth. to sb./sth. verb —, assigner qqn./qqch. à qqn./qqch. v, assign sth. to sb. verb —, céder qqch. à qqn. v, account assignment n —, task assignment n —, temporary assignment n —, pin assignment n —, written assignment n —, random assignment n —, special assignment n —, new assignment n —, group assignment n —, legal assignment n —, audit assignment n —, translation assignment n —, final assignment n —, first assignment n —, assignment of tasks n —, volunteer assignment n —, priority assignment n —, value assignment n —, assignment plan n —, sales assignment n —, direct assignment n —, rights assignment n —, completed assignment n —, recruitment assignment n —, assignment procedure n —, partial assignment n —, core assignment n —, commercial assignment n —, signal assignment n —, color assignment ae n —, document assignment n —, difficult assignment n —, ad-hoc assignment n —, challenging assignment n —, ▸ wikipedia, ▾ external sources (not reviewed).

• This is not a good example for the translation above.
• The wrong words are highlighted.
• It does not match my search.
• It should not be summed up with the orange entries
• The translation is wrong or of bad quality.