According to Common Sense Advisory (CSA) Research, the language service industry is on the edge of a ‘disruptive transformation’ that will change the entire process of augmented translation. Partnered with the developments that artificial intelligence (AI) has produced in the translation industry, linguists will have the ability to reach a broader potential.
In March 2017, when CSOFT Founder & CEO, Shunee Yee, spoke at LocWorld 33 in Shenzhen, China, on the Future of Work: Leading translation in a new era, she said, “In the future, linguists will do more than translate – the bulk of translation will be carried out by machines, which will mean linguists can spend far more time on other, more complex issues such as cultural meaning or interpretation.”
Predicting the Impact of Technology
There has been a lot of talk within the translation industry – from clients, language service providers, and linguists – about the role that technology, especially AI, will play in the translation process. Some say it will be the end of human translation, but most others say that while the human role of translation will shift, the human element will never be removed from language. According to CSA research, AI technology benefits linguists in a way most translation technology has failed to.
In the language service industry, most of our technologies are client-driven with a focus on speeding up and lowering the cost of the translation process. We develop termbases, terminology management systems, and glossaries – all of which are tools used to shorten the time a linguist spends with a translation. Meanwhile, linguists are responsible for the upkeep of these tools, learning and managing the technology, and using it effectively – all while facing lower rates.
The Augmented Translation Model
CSA research claims that with the help of Artificial Intelligence, the translation process will be centered around a professional called the “augmented translator”. Similar to how augmented reality allows AI to enrich an individual’s access to relevant information about their surroundings, CSA foresees AI playing a similar role in translation; allowing linguists to have more access to relevant information, and more “context and guidance”.
The following is an excerpt from CSA research, explaining how technology will become more effective for translators in the augmented translation process:
Adaptive machine translation. This technology – currently found in Lilt and SDL BeGlobal – learns from translators on the fly. It adapts to the content they work on, automatically learning terminology and style. It remembers what linguists have previously translated at the sub-segment level, and goes beyond translation memory to help translate text it has never seen before in a way that is consistent with how the individual professional works. Rather than post-editing MT output of dubious quality, linguists see the results as suggestions they can choose to use or not. The more they use the system, the better these suggestions will become.
Neural machine translation. Today NMT requires vast amounts of processing power, but – as the technology matures – it will improve MT’s fluency and ability to “blend in” with human translation. Even if NMT is in the upswing of a hype cycle, it is a major step forward. Many of the major tech players – such as Baidu, Facebook, Google, and Microsoft – and dedicated translation technology providers – such as SYSTRAN and Iconic – are actively developing this technology.
Lights-out project management. Project management can be time-consuming for both managers and linguists. Manual processes such as invoicing and paperwork that eat up valuable time can be automated. When lights-out systems handle these tasks without the need for human intervention, they free up translators, interpreters, and reviewers to focus on their tasks.
Automated content enrichment (ACE). This technology is just catching on, driven by projects such as FREME and commercial offerings such as OpenCalais. ACE will benefit linguists by automatically linking terms to authoritative resources and by helping disambiguate them, which will improve MT. It will open new windows in transcreation by helping them find locale-specific content and resources that can make translations more relevant for the target audience.
Once all of these technologies play together or “talk to each other”, they will be able to learn from the linguists, according to CSA. This will allow translators to control and work with language technology, rather than feeling constricted by it.
With new improvements to AI technology, there is little doubt that it will have a strong impact on the language service industry. It’s possible that we will see the translation process change to the augmented translation model which will put translators in control of the translation process. Whether we see the effects in the near future, or still several years down the line, many are looking at the future of the translation industry with great hope.