Over the past 70+ years and to this day, translation technology has changed drastically as more companies are focusing on ways to improve their tech performance with data that is higher quality and customizable. Consequently, life sciences organizations have been investing more in AI language automation technologies to drive down costs, reduce time to market, improve translation consistency and quality, and streamline workflows across global operations.
Machine translation (MT) and translation memory (TM) are two computer-assisted technology (CAT) tools that have helped drive innovation in the life sciences sector. To better understand these language technology tools and their benefits for life sciences organizations, it’s important to understand how the landscape has evolved since they were first introduced, as well as considerations to take into account when deciding on your translation technology partner.
We’ve come a long way since the first time machine translation was presented in 1947 by Warren Weave, a researcher from Rockefeller Foundation. Since its inception, machine translation and language technology, in general, have taken on new legs in their capabilities. In fact, according to Global Market Insights, the machine translation market is expected to grow from $650 million in 2020 to approximately $3 billion by 2027. This growth is attributed to several factors, including investment in AI globally, demand for localized content among businesses, focus on improving customer service and experience, and the increasing need for cost-efficient and timely translations. This is particularly true for life sciences and healthcare organizations.
So, how has machine translation evolved? To answer this, it’s best to first identify the main types of machine translation:
Machine learning, specifically in NMT, has taken center stage for its benefits in training translation engines to be more intuitive and accurate. While we’ve made monumental progress since machine translation was first introduced, as it is, regulated industries such as life sciences typically require human post-editing (also known as machine translation post-editing) in order to achieve the highest quality of results.
While machine translation has done wonders for life sciences organizations operating at a global scale, it’s not the only progress in translation automation technology for the industry. In fact, one of the reasons machine translation has become so successful and more widely used is the increasing use of translation memory. When translation memory was first introduced in the late 1970s and early 1980s, it was cited as a way to lighten the translation burden on linguists, improving turnaround time as well as machine translation quality. Fast forward to today, and translation memory is one of the most widely used CAT tools for helping companies build data repositories to enable faster and cheaper translations.
For life sciences organizations, leveraging translation memories or data banks of words related to the industry, as well as company-specific jargon, is imperative for ensuring consistent, higher-quality translations. As an industry that relies heavily on acronyms and technical terminology, translation memory is hugely beneficial for life sciences organizations, particularly when paired with machine translation. With higher quality data being collected, and with a growing focus on developing better, automated translation technology, the role of translation memories will continue to change from being primarily a company translation database to a training tool for machine translation.
As the life sciences industry continues to evolve and innovate, translation technology will also continue to improve and adapt to meet companies’ expectations, as well as keep up with the plasticity of languages. More and more, global life sciences companies are looking for technologies that are intuitive, secure, and easily accessible. When deciding on the best fit for your translation technology partner, take these considerations into account:
Drop us a line if you’re interested in learning more about machine translation, translation memory, and their benefits for life sciences organizations. If you’re interested in seeing a demo of our GlobalLink AI portal, you may do so here.