Today’s topic is a slightly unusual one as it’s all  technical authoring for maximum translation benefit, or more simply, writing for translation.

You might already be looking at me with a puzzled expression. Surely, translation happens AFTER you’ve written the text, not before or during?! Well, yes and no.

I’ve touched on this before in my blogs about reducing translation costs and understanding translation memory software, as well as the blog about optimising your content for translation.

Today I’d like to look at it in slightly more detail, as well as introducing a STAR Group tool that could just simplify your technical writing process.

Writing clearly and concisely

This should be an obvious one.

In any technical authoring task, your number one objective should be to write clearly and concisely. Keep your sentences short. Avoid jargon and overcomplicating your subject.

This does not change when you are writing your document for translation.

It just becomes more important.

Looking at potential fuzzy match percentages

I discuss fuzzy matches a lot in these posts, and I always try to avoid jargon. However, I appreciate that the whole concept of a fuzzy match might feel like an alien language.

Today, I’m going to try and give you an example.

Translation memory software works on the basis of analysing similarity between two units of language; usually a sentence.

Using a fuzzy logic algorithm, it breaks down the sentence into its component parts, i.e. words, punctuation marks and numbers.

It looks at each one of these component parts, checks whether it has moved or disappeared from the sentence and combines the results from each component analysis to create a fuzzy match percentage.

That’s about all the explanation I can give you. No, seriously, don’t ask me any further questions on this. Computer science is not my strong point! Plus, every company uses different weightings in the algorithm so they will all get slightly different numbers.

So let’s look at an example.

Loki the cat


I have a cat; his name is Loki.

I have a dog; his name is Rover.

My dog’s name is Rover.

If we consider the first sentence to be already translated, what do the two examples tell us about potential fuzzy matches?

Factually, both subsequent sentences have the same meaning. You possess a dog; you call him Rover.

There are two changes between sentence 1 and sentences 2/3:

  • Dog not cat
  • Rover not Loki

Comparison of sentence 1 and 2: 75% (classed as a fuzzy match)

technical authoring fuzzy match

Comparison of sentence 1 and 3: Less than 30% match (this will be classed as new words)

technical authoring no fuzzy match

Every agency will have a different breakdown of costs between fuzzy matches and new words, but the principle is the same. New words cost more.

If your entire document contains similar issues, costs will be significantly higher than they need to be.

Avoiding errors

We’re all aware that texts that contain errors are more difficult for the reader. Either grammatical errors in long, tangled sentences, or perhaps a sentence that is littered with typing errors.

Both of these also cause issues for the translator. Potentially it is an issue that is amplified by the fact that they are not native speakers of your language and might find it harder to untangle or decipher the mistakes.

It might take the translator longer to complete your translation project and they may be less willing to work on your texts in the future. As well as there being a risk that they will misunderstand part of your text.

So, how does this affect your costs?

I’ve not come across any agency that imposes cost penalties for texts that contain multiple errors, though they may suggest carrying out an additional proofreading step before translation.

The costs come from misunderstandings that lead to further proofreading steps and incur additional costs to correct errors.

Another concern is for subsequent projects where errors have been corrected. Instead of being able to reuse material as pretranslation, your latest project will be considered as fuzzy matches only. This will add a sizeable percentage increase to your technical translation quotation.

Introducing MindReader

This blog is not really about selling, so I’ll keep this section brief. Even with the best of intentions, it can be difficult to write consistently. It’s more likely that consistency issues will only be found at a proofreading stage or that they might slip through the net completely.

For this reason, the STAR Group has developed authoring tools to help; MindReader and MindReader for Outlook.

Like any tool from STAR, the principle is that you only work on content that is new. Think of it a little bit like autocomplete on your mobile. Just start typing your sentence, and the tool will provide suggestions from elsewhere in your document.

If you want to reuse them, you can. If you don’t, you can ignore them.

It can help with consistency in your technical writing, which will improve clarity as well as bringing down potential translation costs.

If it sounds like something you could be interested in, contact one of our team today.

I hope this blog has been useful in giving you some tips for improving your technical writing and lowering your translation costs.

If you want any further information about this, or to discuss a potential project with one of the team, please do not hesitate to get in touch.

Translation memory management is one of those terms that is regularly thrown around by language industry professionals. It often appears on web pages in a list of benefits that your language service provider can offer you. We’re guilty of it ourselves…!

One of the themes of this blog is to decode some of the jargon and to help translation buyers make an informed decision about who they purchase translation services from. We published an Ultimate Guide to Translation with just this aim in mind. It alluded (very) briefly to the idea of reference management; a concept that will hopefully be fully explained today.

So. Let’s go back to basics and define a few of the key concepts involved in translation memory management:

What is translation memory?

Translation memory refers to a software database containing source language content and the corresponding target language translation. These existing translations can be leveraged for new translation projects in order to speed up the translation process and reduce costs.

How is translation memory stored?

Before you can look at translation memory management, it’s important to know exactly what it is that you might be managing! In the case of Transit NXT, the STAR Group proprietary tool, translation memory is stored as language pairs that can be opened and amended using Transit NXT. Other translation memory tools store translation memory in a database file, often in XLIFF or XML format.

I’m not going to lie – the above paragraphs still contain a fair amount of jargon, so to break down translation memory management even further, I would suggest the following definition.

Translation memory management ensures that any existing translations are of the highest quality possible so that you can gain the most amount of benefit from them.

There. Much better.

Formats for translation memory databases

Although I stated above that translation memory is usually stored as XML or XLIFF, this is not always true. It’s true that translation memory software uses these formats, but for companies or individuals working outside of a tool (Yes, they do still exist!), Excel spreadsheets or CSV files are also workable formats. In this case, translation memory management is therefore about manipulating text stored in columns and rows.

What does translation memory management involve?

As a term, translation memory management covers a few different processes to do with storing and updating translations.

For me, the most important consideration for translation memory management would be to look at the first part: storage.

Storing translation memory

Are you storing your translation memory in a format that can be easily leveraged? If you are still working with XLS or CSV files, these can become unwieldy very quickly and you might not be able to enjoy the benefits of fuzzy matches.

Are you storing your translation memory in a format that can be easily navigated? For example, in the case of Transit NXT language pairs, are you using a folder structure that has a logical hierarchy?

Managing translation memory on a large scale

Here at STAR UK HQ, we have working relationships with customers that span nearly the entire lifetime of the company (over twenty years at time of writing). As you can imagine, we’ve done many millions of words for them, and translation memory management is important because of the sheer volume of reference material available to our team.

We need to ensure that each translation can make use of every scrap of material that we have for that customer, but at the same time, we cannot send several gigabytes of data to our team for each project.

Should we organise translation memory by document types such as manuals, press releases and contracts? Should we organise chronologically? Should we organise by text types such as technical, marketing, legal and financial?

There’s no correct answer to that question. For us, translation memory management is about ensuring maximum leverage of existing material, so we organise by language, then chronologically.

For some customers, we further distinguish between text types, but a customer’s press release may still contain technical terminology so making the technical manual translations available as reference will be helpful for terminology.

So it’s just about a sensible folder structure?

Well, no, not really. Translation memory management is also about ensuring that your reference material is the best possible quality.

What does that mean in practise?

dictionary definition

Terminology preferences

Many of our clients have strict terminology preferences. Sometimes these take the form of approved terminology lists that are sent before translation begins. However, sometimes preferences only come to light when signalled by a customer reviewer.

In these cases, it is important that any disallowed terms or preferred terms are updated throughout the existing reference material so that these are not used for any future translations.

A project manager responsible for translation memory management for that customer will comb through the reference material and will update the translations for every occurrence of the term.

Updating translations based on corrections

Translation memory management also involves correcting translations in the case of errors. Although a thankfully rare occurrence, I wouldn’t be doing my chosen topic justice if I omitted this one.

If an inaccurate translation is suggested as a fuzzy match, it is possible that the error will be included in the new translation and will propagate through the reference material. At this point, it is far harder to resolve as the error may appear in so many locations.

Customer corrections can also sometimes relate to preferential changes (a far more frequent occurrence). We understand this one well – your brand needs to be the same across languages and as the customer, you know it best.

In this case, we need to update the reference material so that we continue to learn what the customer likes and so that they don’t need to make the same correction twice.


Remove duplication

The final task that we class as translation memory management is to remove duplicate, or variant, translations from the database.

The principle of translation memory is that you only work on what is new. So, in other words, if a translation exists, you can use it in your text without needing to start again. However, sometimes the practicalities of the industry get in the way.

For certain customers, workflows and internal deadline pressures mean that certain translation projects need to run concurrently. Where there is any overlap between projects, it is possible that a duplicate translation will be created.

Translation memory management therefore involves finding these translation variants and choosing one translation to use for all future projects. This could sound like a needle-in-a-haystack task, though Transit NXT has a handy variant checker for just these occasions.

Who should be working on translation memory management?

Really, it’s THE question, isn’t it? All of the tasks listed above are important for ensuring that translations are high quality, but potentially they can fall through the gap of where responsibility lies.

Although the customer is best placed to make preferential and terminological changes to their material, they often do not have access to TM tools and the reference material.

In my humble opinion, translation memory management is therefore within the remit of your translation supplier.

Your translation supplier will often have tools at their disposal to simplify some of these tasks, as well as quality assurance checkers to make sure that every instance of a change has been made.