E.g., 11/12/2019
E.g., 11/12/2019

A New Wave of Technologically Empowered Translators

By: KantanMT

In recent years the translation and localization industries have experienced important shifts in the area of technology development and technology adoption. The advancements in web applications, internet speed and price reductions for Translation Memory, Machine Translation, and Translation Workflow Management Systems have made it easier for an increasing number of language service providers (LSPs) to integrate productivity enhancing tools into their technology mix. Yet, while more and more LSPs start to adopt these technologies, many of their teams are not yet fully proficient at maximizing the benefits that these technologies can offer their business.

Changing Times:

In the past, there were limited opportunities for translators to experiment with translation technologies – primarily because technical skills were not seen as being overtly necessary compared to crafting linguistic/translation skills. And while classical translation/interpreting skills will always come first, times are definitely changing and those working in the language industry need to be adaptable to new trends – in particular the growing use of translation technology.

To be ahead of the game, translators need to be equipped with the right level of knowledge and experience using these new technologies. The digital age has had a huge influence on the way the localization industry operates and it’s the responsibility of both LSPs and translators to ensure they are up-to-date on current industry tools.

Empowered Learning

Students are becoming increasingly aware of this need to be educated about translation technologies and are now more actively seeking courses which will increase their proficiency in these areas. It is no longer surprising to see third level courses advertise CAT tool training and/or Machine Translation technologies on their prospectuses.

Since the rise of Translation Memory in the nineties, increasing numbers of translators have become proficient in using TMs and are familiar with many of the industries more popular CAT tools. Machine Translation is now gaining ground as more and more LSPs are utilizing this technology to offer more value to their clients. Because of this, increased levels of education is necessary.

The empowered translator understands the concepts of TM and MT, and their applications, but not necessarily SMT statistical models and algorithms. Statistical Machine Translation is highly technical at its core and involves a great deal of study to master, but if we remove the technical aspects of the science and focus on teaching students how to apply this technology to their work then perhaps they will take on a more empowered role when working with MT based projects and output.

The use of online self-serve platforms like KantanMT as a teaching resource in third level institutes is making it easier for translation students to develop an understanding of the output of Machine Translation, and also the process of developing, customising and improving MT systems, without the need for any technical or prior knowledge. This is the beauty of self-serve MT platforms – students can rapidly build MT systems, and develop a good understanding of Machine Translation development, without the need to fully understand the algorithms or statistical processes behind the system.

Cloud Technologies and Teaching:

Uwe Muegge wonderfully explained the benefits of using cloud technology in his February GALA blog post, which is one of the key reasons that Universities such as UCL and DCU are choosing KantanMT as their teaching platform. Cloud-based technologies make it easier for Universities to offer students access to the latest technologies as it immediately reduces the costs and time requirements needed to set up software, and accounts are accessible from any device and from anywhere in the world. This accessibility is helping a growing community of empowered translators learn about translation technology and apply this knowledge to their work.

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