The revolution in technology that we’ve witnessed over the past two decades has affected just about every industry in the world. With the surge of rapid developments, the way we live and work has changed almost beyond recognition, and the translation industry is no exception.
A few centuries ago, the main mode of translation was through ink and paper. Now, most translations take place on computers, and the transition from hard copies to electronic copies has made the lives of translators so much easier. Hence, it’s no wonder that the translation industry experienced colossal growth driven by an increasingly connected and global world – in 2021, it was valued at $56 billion.
But what are the exact technologies and developments that changed the nature of translation the most? This article explores the rise of AI-based translation, CAT tools, termbases, digital dictionaries, and the changes in machine translation. Read on to learn more.
Termbases and digital dictionaries make for a vast field. These two tools share quite a few similarities and both can be incredibly useful. In short, a termbase is a collection of different words and phrases as well as their definitions and other related linguistic information that people might be looking for when checking particular words or phrases. Their main objective is to ensure that terminology is used in a consistent way.
Digital dictionaries are resources that show the exact translation of individual words to and from another language and usually provide less additional information than termbases. For instance, if you Google “Puerto Rico translation,” a digital dictionary will inform you that “puerto” means “port” in Spanish, and “rico” means “rich.”
Both termbases and dictionaries have always existed in some form, but digitalization has made them easier to use and more accessible. Nowadays, you don’t have to spend ten minutes searching in a paper dictionary for the translation you’re looking for. All you need to do is type the word or phrase, hit “enter” on the keyboard and have the tool do the work for you.
One of the most recent innovations has been the development of AI-based translation systems. These systems are designed to “learn” how to translate a text through machine learning as they process language data and progressively improve their output quality.
The AI-based translation is much faster than traditional translation services – translating texts manually can take hours upon hours, while an AI-based service can get you the translation in a shorter time, and you’re likely to pay much less for it than you would have to if hired a human translator. Accessibility is another huge advantage of AI-based translation, as it is available for just about any device, whether it’s a laptop or a smartphone that most people always carry in their pocket.
Although they’re not perfect, they already produce very good results, and their capabilities and performance are improving every year. For example, Google and personal assistants such as Siri or Alexa are able to do translation for you in the blink of an eye. While they’re not always hundred percent accurate, the improvements are being made constantly.
Computer-assisted translation (CAT) tools are a significant part of the advancements that help translators stay on top of their work and keep up with the demand for translations as well as improve their efficiency. Softwares such as MemoQ or SDL Trados are probably the most known on the market, but there are also many other translation providers that have developed their own computer-assisted translation solutions.
Text extraction: pulling text out of source documents in multiple formats, and machine translation: performing automatic translations that are then post-edited and approved by a translator are just two examples of tasks CAT tools can perform. They can help ensure consistency across all translations, reduce costs as they make the translation process much more efficient, and reduce the amount of time needed to translate a given text.
A lot has changed in machine translation over the past decades. While the 1990s saw the development of statistical techniques for machine translation, by 2016 came the era of neural machine translation. NMT is designed to learn over time based on the input translations, and as it learns, it becomes more accurate. It’s capable of producing some of the most precise translations among all MT technologies available today. The more the engine is trained, the better the translation it can produce.
Unlike other approaches, neural machine translation utilizes a large neural network that uses artificial intelligence to operate in a way that’s based on how the human brain works. It’s one of the most advanced forms of machine translation that are currently available and is being widely used for professional translations.
However, some people argue that one of NMT’s main disadvantages is that the source-text phrases need to be very clear and coherent to obtain a quality translation. NMT can also encounter difficulties when working with highly technical language or when the input text is saturated with rare words and proper nouns. To effectively deal with these issues, human interaction is essential.
Last but not least, it’s also worth speaking a little about connectors. In the translation industry, it’s software that connects two different systems to allow for content sharing without the need for human intervention. With their help, users can send and import translations directly from the system they are using. Some of the main benefits of connectors include:
- Ability to avoid common copy-paste errors,
- Reduced content preparation time,
- Improved security with HTTPS-encrypted data transfer,
- Eliminating the risk of losing data.
As you can see, translation technology underwent many significant changes in recent years, and today it is an area that is transforming rapidly in terms of research and development. There is also no doubt that modern translators have a lot of new tools available to them. The wide termbases and digital dictionaries, AI-Based Translation, CAT tools, machine translations, and connectors all help them work faster and more efficiently.
While it’s true that many machine technologies are still far from perfect, they can still be used to our advantage and make our lives easier. The question is not whether or not to use these technologies but how to make the most out of the various tools available.
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