Artificial Intelligence, mainly referred to as AI, is seemingly touching every industry and aspect of modern life.
Farming, Insurance, Arts and Entertainment, Education and Healthcare have all such major AI developments and breakthroughs in the last 2 years particularly.
In this article
- 1. How is AI Impacting Translation?
- 2. Is AI Disrupting Translation Services?
- 3. What Don’t People Know About How AI is Helping Translation?
- 4. What Are Some Good Examples of Translation Services that Uses AI?
- 5. What Trends Are Emerging with AI in Translation?
Translation services, albeit a small cog in the wheel of the advertising industry, is being dramatically impacted by AI developments and new technologies.
This has specifically impacted Voices, as the world’s #1 voice marketplace, we provide translation services to thousands of companies around the globe.
Voices has trusted the services of Keylingo, a business-to-business language services provider (LSP). Keylingo’s area of expertise is to help its partners communicate effectively and help them create content to help audiences “understand and feel included”.
Keylingo leverages a combination of machine and human translation to keep costs affordable for companies.
We caught up with Richard Carroll, Keylingo’s Managing Director, to understand how AI is impacting translation services and where the world of translation is headed because of AI.
Below is our Q&A with Carroll.
1. How is AI Impacting Translation?
Artificial intelligence (AI) is used to simulate human behavior, and in the translation industry, AI focuses on developing tools and solutions capable of performing tasks to simplify and optimize the entire translation process.
AI has been embraced in the form of Machine Translation (MT), which helps translate a higher volume of content in less time than human translation. When it comes to translation, AI is used to help us work smarter while improving translation quality throughout the process. This means content can be pushed to market at a much more rapid pace without sacrificing quality.
AI directly leverages deep machine learning neural networks to determine how to properly translate your content by interpreting the intent of that source content. The result is that AI translation acts more in line with how a human translator works, rather than just a bilingual dictionary. The artificial translation isn’t about removing the need for human translators, but rather supporting them, and simplifying the process from A to Z.
2. Is AI Disrupting Translation Services?
Artificial intelligence in translation is a hot topic at the moment, following such a boom in real-world use of the technology. It is great to work with very common Latin-based languages such as Spanish, French, and even Italian. But with more complex ones, such as Arabic or German, there are some points to take into account when it comes to quality.
There have been many advances in applying AI to language translation. These advances allow computer-aided translation (CAT) software like translation memory (TM) and MT to perform translations more efficiently and at a higher quality level, which is a benefit to translation firms and ultimately their clients.
The demand for translation is rising, given our global economy, and CAT software can add a considerable amount of value to the process.
However, translation software hasn’t risen to the level of understanding the subtlety of all types of language. Also, if the original content was poorly written, the software may not have a defined way to communicate the intended meaning whatsoever.
This issue is giving rise in some parts of the industry to a new role: Post-translation editor. Typically, content writers work hand-in-hand with editors to polish, refine and enhance their writing. A post-translation editor can do the same thing for content processed by machine translation.
It’s important to highlight that there are areas where machine translation isn’t advisable, including most areas of marketing and legal content. Those two areas require an in-depth understanding of more than language rules, and AI hasn’t reached a level that provides that type of insight.
3. What Don’t People Know About How AI is Helping Translation?
Thanks to AI, we can reduce costs, while saving valuable time. The efficiency of the AI when translating will always depend on the kind of translation project you will be working on.
There are lots of Cloud Translation Software platforms available, each with its own strengths and weaknesses. NMT (Neural Machine Translation) represents the most widely known use of AI in translation. We already see powerful engines from machine technology providers like Google, Microsoft, and Amazon.
Due to COVID-19, there is a trend of focusing on distributed work and the minimization of interpersonal contact to essential occasions. Because of this, several companies rely on AI tools to facilitate communication across language barriers.
That increase in demand has in turn accelerated the development of machine translation technology. Looking back to only five years ago, technologies have moved from rule-based and statistical models for translation to Neural Machine Translation (NMT) based on neural networks that seek to deeply mimic the way a human translator would handle and translate documents.
As more focus is placed on the sector, the pace of development and involvement of humans-in-the-loop will continue to increase and so will the efficiency and accuracy of the machine translation software.
Twenty-first-century enterprises look for high-quality and immediate language deliveries as they handle big data. Advanced artificial intelligence has now made it possible for companies of all sizes to compete in content publishing using specialist machine translation, particularly when they focus on specific languages and use cases. That has also had the effect of opening up opportunities for innovators and entrepreneurs to provide specialized solutions to meet the increasing, globalization-driven demand.
4. What Are Some Good Examples of Translation Services that Uses AI?
There are several free Machine Translation Tools existing in the market that are available worldwide such as Google Translate, Bing Microsoft Translator, DeepL, and Reverso Translation, and others paid such as memoQ Translator PRO, Systran Translate PRO, Smartling, Crowdin, TextUnited, Amazon Translate, and Memsource.
5. What Trends Are Emerging with AI in Translation?
It is true that machine learning and AI become must-have capabilities in every industry, but it is still unknown how exactly they will shape the future.
Sometimes, we hear that Machine intelligence will exceed human intelligence and go beyond our control. But no one can confirm it, yet.
The AI that we have now is called “weak AI” or “narrow AI.” All existing AIs are narrow. No matter what technology you take, AI is only focused on one narrow task, whether it is machine translation, speech recognition, flying planes, or driving cars.
“Strong AI” (or “full AI,” “general AI” and “deep AI”) is still a sci-fi concept, but we are getting there. Strong AI will combine multiple AIs together and is said to be about as capable as humans. It is as if Siri one day started understanding any instruction, including those given in a strong or unusual accent, but additionally and more importantly, she would be able to create her own music (based on your musical preferences), accurately forecast business trends and choose the best-fitting clothes for you online.
The third, and the most powerful version of AI, is called “super AI” (or ASI). It is something we can only speculate about. The definition is simple: Super AI would surpass all human intelligence, and its limits will be unknown and barely conceivable by a human mind.
We can only speculate about the future, but no one knows how far AI will go, what form it will take, and what will be the next ground-breaking technology to change the world in the same fashion as the internet, social media and big data did. However, instead of being afraid of what the unknown future holds for us, we can assume an explorative and inquisitive approach.