Discover the latest trends in the translation industry

The translation industry is going through a period of profound transformation driven by technological change. Therefore, opportunities such as using machine translation are already a reality thanks to increasingly accurate translation software. 

The irruption of these technologies has provoked a division between those who embrace futuristic proposals in the translation industry, and those who are more skeptical about the role technology should play.

What are the key trends that will significantly alter the professional translation industry in the coming years? Let’s analyze it.

 

A quick look at the last few years in the translation industry

There is at least one indisputable conclusion to be drawn from the past few years in the translation industry: the sector growth of language translation, driven by an increasingly connected and global world. Indeed, the translation industry has gone from being valued at 49 billion in 2019, to over 56 billion in 2021; an increase of more than 5 billion in just two years. There is also talk of a 40% development in the industry during the COVID-19 crisis.

Beyond these figures, the incorporation of technological translation engines and the move towards machine translation have been a real revolution for the translation industry. 

Thus, globally in 2019, the volume of translations carried out by machine translation engines already surpassed that of professional human translators.

This automation has induced a number of transformations in the industry, which translation service providers (TSPs) have had to adapt to. 

Accordingly, the incorporation of technology has played a key role in the following processes:

  • With machine translation, the use of human translators is being minimized and their role is changing. While some platforms speak of eliminating human intervention completely, this point has not yet been reached, especially when it comes to translations requiring the highest accuracy. However, the adoption of digital translation tools has meant that human agents have had to adjust their work and behavior, eliminating obsolete structures and actions.

The service diversification for TSPs is also among these transformations, now offering, for example, complementary services to machine translation such as language detection services.

  • Thanks to digitalization, the machine translation industry is able to offer faster and cheaper translations. This is only possible thanks to the digitalization and automation of part of the processes.

Again, looking to the future, there is talk of possibly eliminating marginal costs in translation: once the translation structure has been set up, producing new content is unlimited and free of charge.

  • The incorporation of Artificial Intelligence in translation engines has made it possible to take speed and accuracy a step further. Possibilities such as deep adaptive machine translation mimic the work of a human translator more and more precisely, including more complex issues such as style and expressions.





What does the future hold for the translation industry?

Instant translation: Google vs Apple

Google and Apple are two key companies that are providing advances in the translation industry. In particular, these two companies are competing for the launch of more precise instant translation software. 

On the one hand, Apple is incorporating this in iOS 15 beta, which allows you to instantly translate any text even in offline mode

On the other hand, Google has gone even further with its Pixel 6 line, expanding the possibilities of instant translation by providing text, voice and image translation, again without the need for an internet connection.

 

A balance between machine translation, post-editing and human translation

In today’s current translation industry, the following three approaches coexist: 

  • Human translation. This is the most reliable and accurate option nowadays, especially for creative content (literary translation or copywriting, for example) or more technical content (legal texts or user manuals). In most cases, human translators use computer-assisted translation software to control the quality of their work.
  • Post-editing. A hybrid between machine translation and human translation in which the human translator receives the machine translation and edits or corrects it when necessary. 
  • Machine translation. Translations carried out 100% by a machine. 

In the coming years, these three approaches are expected to achieve a balance. On the one hand, the machines’ role will continue to be that of streamlining and facilitating translations (offering cheaper services as a result). 

The generation of increasingly useful databases and the incorporation of Artificial Intelligence algorithms will expand the possibilities for this type of translation. For example, developing options for precise predictive translation will be possible.

On the other hand, the role of human translators will be moving closer to supervision and use of unique human capabilities, such as using jargon or colloquialisms, creative writing or interpreting slang. 

In addition, the industry will move towards a machine translation post-editing (MTPE) model: editing and proofreading translation results produced by a machine. The consulting firm Gartner predicts that human translators’ work will be 75% linked to MTPE by 2025, while the European Commission claims that 78% of Language Service Providers (LSPs) have already started to shift their work to this area.

As an example, at Pangeanic we are trying to advance precisely towards this balance with our machine translation services:

  • On the one hand, we provide translation solutions using state-of-the-art technology. Our translation engines use powerful neural networks in our private and secure cloud or in our clients' own infrastructure. We also have API technology and custom machine translation engines, which can be customized and applied at different levels of deep learning aggressiveness and impact through training programs for machine translation engines.
  • On the other hand, we provide the supervision, experience and linguistic expertise of our more than 5000 certified translators.

 

Language data

Having relevant databases is one of the necessities for developing machine translation. In the coming years, this area is expected to develop in a number of ways: 

  • There will be more accurate databases thanks to more efficient elimination of repetitions, errors or irrelevant attributes. Progress will be made towards more evolved techniques for selecting and grouping data.

In this regard, the search for human talent will focus heavily on this area.

  • Doubts and tension about language data and copyright issues could entail new regulations and best practices.
  • Although language data is currently controlled by a few large companies, it is possible that this resource will move towards a cooperative and circular economy model.
  • The advances in increasingly complete and comprehensive databases will also allow for translating languages that still defy machine translation, provided they are accompanied by a demand for translations in the market.

 

 

 

 

Custom translation engines

Advances in the accuracy of machine translation will also go through constructing custom translation engines for organizations, progress driven in turn by the creation of quality databases.

Among the advantages of having custom translation engines are greater flexibility and control of the translation results. In turn, customization will be closely linked to translation engine training with machine learning.