
Phrase and beyond
Translation management
Translation technology has been around for more than 50 years now, but as our world has become increasingly interconnected, it’s only grown more essential.
A report by Nimdzi Insights found that the current language technology landscape includes more than 700 solutions. Given this diversity, how do you find a translation tool that best suits your business needs?
The first step is to gain a solid understanding of what translation technology is and how you can leverage it. Keep reading to find out.
Translation technology is the use of software tools that support the process of converting written text from one language to another. As is the case of most work aided by technology, translation technology tools can increase productivity, accuracy, and overall effectiveness.
The term “translation technology” encompasses everything from translation memories and terminology management tools to machine translation (MT), virtual interpreting technology, and even voice-to-text technologies.
Before the emergence of translation technology, translation was done manually, with translators consulting paper dictionaries and using their best judgment.
The negative impact on business was substantial as a result of:
The birth of translation technology changed it all. Tools such as translation memories—which store previous translations to inform and expedite future projects—and translation management systems help automate repetitive processes and increase control.
Today, translation technology tools allow businesses to:
Before we go into more depth on the various types of translation technology, let’s go back in time and examine how translation technology evolved.
Some of the techniques used in modern translation technology can be traced back to the 9th century when an Arabic cryptographer named Al-Kindi developed the method of frequency analysis that is still used today.
However, it wasn’t until the mid-20th century, when computers became available and affordable, that translation technology truly began to take shape.
Here’s a rough overview of the evolution of translation technology:
In this fast-paced, ever-connected world, consumers demand seamless experiences that are as user-friendly and accessible as possible. They also want high-quality products and services that are culturally sensitive and adapted to their needs.
The process of adapting a brand’s message, look, and feel to a given culture or location is called localization. While localization may involve different aspects, such as product packaging, web design, or business strategy, it’s the culturally aware translation of a brand’s message into a specific language that is at the core of successful localization.
In the context of the information economy, this can mean having to deliver dozens of content types, in multiple languages, to a diverse range of audiences. Translation technology enables businesses not only to meet these challenges but also to maximize translation spend by increasing speed and quality while reducing cost.
Today’s decision makers who have to strike a balance between the expectations and demands that come with globalization while keeping a close eye on costs and productivity can rely on translation technology to help them deliver on all fronts.
Translation technology allows companies to go global quickly, easily, and affordably by enabling them to streamline the entire localization process. It provides them with scalable, efficient solutions that can help them reach new markets faster and more effectively than ever before.
Modern translation technology is constantly evolving, with new innovations coming every year. What follows is a (non-exhaustive) list of the most popular translation technologies.
CAT tools are software applications created to support translators in their daily work. CAT tools use databases of previous translations (usually from a specific source language and target language) as well as frequency information, segmentation data, and a wealth of other resources to aid the translation process.
Visually, a CAT tool interface usually displays two columns or panels: One shows the source text, and the other displays the target text. Typically, the tool will segment the source text into chunks—sentences or paragraphs—to make it easier for the translator to keep track of the flow of information.
CAT tools usually have a large number of functions, such as:
CAT tools have revolutionized translation technology, making it easier for companies to optimize the translation process and handle large amounts of content in a more efficient way, saving both time and money. For translators, the main benefit is that they can use the time saved on repetitive tasks to focus more on the translation itself.
CAT tools are also highly scalable and customizable, making them invaluable for any business seeking to streamline its translation process based on the specific needs of its content and target audience.
Machine translation is an automated system that allows for the production of translated content without human intervention. As described earlier in this guide, machine translation is not a new phenomenon. However, the advances in technology that have taken place in recent years have led to a rise in the use of MT. Machine translation differs from CAT tools in that it doesn’t rely on human input but produces translations entirely on its own.
Since their inception, machine translation engines fall in one of the three below categories:
Until 2016, MT systems were based on a statistical approach. Today, most machine translation engines are neural.
The quality of machine translation output varies depending on factors, among which we count:
Considering the above, companies can choose whether to use raw machine translation (i.e., completely unedited) or to hire human translators to refine the output, depending on their goals and needs. The latter is called “machine translation post-editing (MTPE),” and it can be either light or full.
Remember: For raw machine translation, it’s vital to use a state-of-the-art MT engine that is highly trained and powered by AI technology.
Thanks to modern technology, it’s also now possible to identify the quality of machine translation output to focus post-editing resources where they are most necessary. This is called machine translation quality estimation (MTQE).
Different types of texts will be more suitable for a lower level of editing. For example, a website’s FAQ page may require light editing; however, a press release that will directly impact the brand’s reputation should go through a full post-editing process.
By the same logic, sensitive content such as financial statements should always be handled by human translators. As a rule of thumb:
Because machine translation is nowadays integrated in most modern CAT tools, you can aid the work of post-editors with CAT tools’ features such as glossaries, term bases, and translation memories, as well as brand books and style guides. This makes it very feasible to keep brand voice and key messaging consistent across cultures and languages with MTPE.
A translation management system (TMS) is a software platform designed for translation project management at scale.
It streamlines the translation process from start to finish, creating a workflow from the initial request to project completion, and allowing users to plan, assign, and manage translation projects in an organized manner.
TMS solutions vary according to the needs of users (e.g. some are cloud-based and some are on-site). Nevertheless, in general, they all include a core set of features:
The best TMS solutions are flexible enough to allow users to create their own workflows and customize the software according to the needs of specific projects, departments, and teams. They are highly scalable and grow together with your business.
Because of the diversity of translation software out there, companies can pick and choose exactly what kinds of solutions work best for them from a solution provider. However, how do you tell whether a translation technology provider is the right fit for your organization?
Translation technology providers must not only offer the ideal mix of functionalities and tools; they need to be flexible enough to integrate with existing systems while supporting scalability. You also need to assess whether their technology is intuitive for your users.
Creating a translation technology request for proposal (RFP)will help you articulate the features and benefits of your ideal translation technology provider. Doing so will allow you to sift through the plethora of providers and point out which ones meet all of your requirements.
Before creating the RFP, some points to consider when you’re evaluating potential providers include:
Translation tools are already much more nuanced than they were even just a couple of decades ago thanks to machine learning. Translation technology will only grow stronger as artificial intelligence continues to advance.
However, translation will never be completely automated because human translators and specialized machine translation tools have their own advantages that complement each other well (e.g. humans are great at creatively thinking outside the box, and AI is ideal for automating repetitive tasks).
As a result, experts agree that the future of translation will combine human intelligence and AI-powered machine translation to produce the best results. In the end, human translators and AI tools will work together as a single translation team with each member playing its distinctive role. We will likely transition from computer-assisted human translation to human-assisted computer translation.
Machine-translation post-editing will ensure that AI-generated translations are accurate and fluent, while human translators will make the final creative changes to cater for specific audiences.
The horizon looks bright: Translation technology will continue allowing translators to focus on more complex translations, leaving the tedious and repetitive tasks for AI-powered tools.
It’s no longer a question of whether or not to use translation technology; the next question is: Which one?
Last updated on March 31, 2023.