Artificial Intelligence and Translation Technology by Jost Zetzsche
I recently asked all the translation technology vendors that came to mind this question:
What are the areas in which you see artificial intelligence playing a role in your technology and/or in the translation-related technology of other vendors?
Why ask that? Well, there’s been a lot of talk about artificial intelligence (AI) in technology in general. In the world of translation, we’ve talked about it in relation to machine translation (MT) in particular, but of course there’s a lot more to say about AI and translation than just how it relates to MT. I was curious to see what’s on the forefront of the minds of the developers of technology that you and I use.
The majority of translation technology vendors I contacted responded (many more responses are listed online). You’ll see that the answers below (listed alphabetically according to vendor) are all over the place, but I think you’ll end up learning a lot in the process (I did), including that AI is much more than “just” neural machine translation. Please note that the answers below are in the vendors’ own words.
ATRIL
The application of Deep Learning to translation, in the form of neural machine translation (NMT), is clearly the main role that AI is going to have in the translation sector in the short term. The availability of accessible open-source NMT projects has resulted in a proliferation of language services providers adding NMT to their service portfolio, perhaps as a way of demonstrating their technical prowess. That said, given the vast amount of training data required to train high-quality NMT systems, it may still take some time for NMT to have a real impact in the industry.
In the short term, we expect NMT to be integrated soon into most competitive computer-assisted translation (CAT) tools, with translator workflows slowly shifting to post-editing. We also expect other applications of AI to play a role in two other aspects: a) in the gathering and cleaning of training data for NMT; and b) in more sophisticated quality assurance tools.
ILANGL
We believe artificial intelligence in the translation industry can be used in these areas:
- Estimating localization quality.
- Helping to quickly select the best linguist for a particular job.
- Analyzing the resource workload and helping the project manager to manage and optimize the resource pool of linguists.
- Partially or fully replacing the project manager when dealing with complex localization workflows.
KANTANMT
There are numerous areas in which AI and machine learning will be used to enhance and improve localization workflows. More importantly, AI and machine learning will be used to improve business efficiencies and operations. These will lead to faster and more intelligent execution of localization workflows using fewer resources and costs while improving profitability. Here are a few areas to consider:
- Demand forecasting.
- Predictive workflow planning.
- Recommendation engines for optimal workflow selection.
- Alerts and diagnostics from real-time project management monitoring.
- Proactive workflow health management.
- Project performance analysis.
- Dynamic pricing (based on project factors).
- Workflow traffic pattern and congestion management.
- Risk analytics and regulation.
- Resource utilization analysis.