Artificial intelligence (AI) is more popular than ever in business. Companies in every industry now use it to deliver higher-quality outcomes in less time—the translation industry included.
Let’s walk through what AI translation is and how it can maximize translation ROI for your brand.
What comes to mind when you hear the term “AI translation”? If machine translation (MT) does, you’re on the right track.
AI translation also encompasses large language models (LLMs) and various other machine learning, deep learning, and natural language processing (NLP) techniques.
As a result, AI has applications across the entire translation workflow, both before and after the translation stage.
Here are a few use cases for AI in the localization process.
LLMs are trained on datasets that contain billions of parameters. Using NLP, they’re able to identify linguistic patterns and semantic relationships. This enables them to understand and replicate human language, which comes in handy for pre- and post-editing.
For example, Smartling’s GPT-enabled portal, Smartling Translate, takes your brand’s voice, style, and terminology into account to produce high-quality, accurate machine translations instantly. In our GPT and Large Language Models webinar, we showed how you can use Smartling Translate to:
Using GPT to pre-edit content in the source language ultimately means higher-quality translated text output. But you can also use large language models to “smooth” completed translations, improving their accuracy and fluency.
Neural machine translation (NMT) is currently the most prevalent form of MT, and we also see a lot of promise in the use of LLMs to aid in the translation process. Both use neural networks that mimic the way the human brain works.
Rather than swap out individual words based on pre-set rules, NMT engines consider context to translate words correctly. They learn over time, which allows them to translate more accurately. Overall, they’re better than their predecessors—statistical MT models—at capturing the intended meaning of source text.
An example of machine translation in action is Smartling’s Neural Machine Translation (NMT) Hub, which is a cloud-based MT model driven by AI. The NMT Hub uses AI to select the best MT engine for your content, which results in the highest quality MTs in a private and secure environment.
AI can reduce both your manual workload and your publishing time by automating various project management tasks, such as:
Smartling’s Dynamic Workflows use AI to route content to the right step in the process based on conditions you set. As a result, Smartling customers have been able to automate 90% or more of their efforts.
As you can see, AI has extensive capabilities as it relates to translation workflows and efficiencies.
However, that doesn’t mean you should stop working with professional translators altogether.
In episode one of our LanguageAI Reality Series episode, Andrew Batwash, our Associate Director of Language Services commented on the following:
You can design AI systems to have effective and meaningful human intervention. What we want to do as a service provider in the language services space is really think about where the human comes into the human-in-the-loop system. How do they add value? And is it in the right place at the right time to generate the output that the customer is looking for?”
“A lot of the conversation is like, we're taking work away from translators and we're going into this fully automatic world. That's not really what it is. It's going to be something more in the middle. Those systems, in a lot of ways, are going to help people be more productive.”
In part, that productivity advantage stems from progressive advancements in the functionality and reliability of AI tools used for translation work.
The higher the quality of training data (and user input), the more reliable AI is.
The opposite is also true. This is why custom MT engines are so valuable: They’re trained on language specific to your company and domain via your translation memory and glossaries. As a result, they can output accurate, on-brand translations.
In contrast, it’s also why some large language models struggle with content translation. Many have limited training data in non-English target languages, making it more challenging to generate highly accurate, culturally-relevant translations.
The situation is similar to the AI used for process automation, which learns from patterns in training data. Whatever patterns you set, the AI will continue—for better or worse.
Of course, your input matters, too.
Give an LLM a poorly engineered prompt, and it will be harder to get good translation results. Give an MT engine a low-quality piece of content, and the translated version will likely have some of the same quality issues.
AI, in general, is a quickly developing and rapidly changing technology that has had a huge impact on the quality of translation software in recent years.
Important improvements and developments include:
Why leverage artificial intelligence rather than sticking to the traditional human-driven translation process?
On any given day, your to-do list could include most or all of the following:
All of this can take a good amount of time when done manually, and you probably have other responsibilities too! Incorporating more AI into your processes is the key to freeing your time to focus on the highest-impact activities.
MT costs a fraction of the price of human translation.
The latter typically costs $0.15 to $0.30 per word, but MT often costs as little as $0.000010 per character. This means cost savings of tens or even hundreds of thousands of dollars per year.
You can then reinvest that money into high-priority language translation projects or use it to support other business initiatives.
The time and cost savings associated with AI translation solutions also mean that these solutions are more scalable. You can expand into new markets and translate more of your content faster. And you can reinvest the money you save into larger localization efforts.
You might think professional translators have the ultimate advantage because they can capture emotion, consider context, and apply local and cultural expertise to translations.
But incorporating AI into your processes can contribute to quality as well.
Automated quality checks can bring your attention to issues that need fixing. Quality estimation algorithms can alert you to translations that need review or revision, and help you quickly identify content that’s ready for publishing.
Of course, you’ll want a solution that strikes a good balance between quality, cost, and speed. But also consider the following:
Even with these criteria in mind, though, it can still be hard to pick because of the ever-increasing number of AI-powered tools out there.
Now that you have a better understanding of what AI translation is and its benefits, here are some AI-powered tools and services to look into.
Smartling has one of the most advanced translation management systems (TMSs) in the localization industry, enabling you to leverage AI across the entire localization process.
It’s also one of the most highly rated by customers—it was rated as the #1 pick for enterprise translation management on G2 for 20 quarters in a row.
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DeepL is among the most reliable neural MT engines in terms of consistent translation quality. It has several advanced features that make maintaining high quality standards easier such as the ability to choose from lists of alternative words and view definitions of words in the source and target language.
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Google Cloud Translation API is the enterprise-friendly sibling of Google Translate and has two editions.
The Basic edition is mainly for short-form and user-generated content like social media content or chats. The Advanced edition is better suited for translating long-form content and performing various types of customization.
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Copy.ai is a broad-reaching solution that focuses on helping sales and marketing teams use generative AI for tasks like creating blog posts and writing emails.
Creating multilingual content using an AI translation solution is one of the many features that Copy.ai offers.
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Microsoft Bing Translator is Microsoft’s version of Google Translate, one of the most widely used translation apps.
The biggest benefit here is that Bing Translator is free for both in-browser and mobile app use.
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Which of these options should you go with? Luckily, if you integrate top MT engines with Smartling, you don’t have to choose. You’ll receive these engines’ quality translation results while enjoying additional benefits from the industry’s most powerful TMS.
These benefits include MT customization that uses your glossaries and translation memory to apply your brand terminology, style, and preferences, as well as AI features that improve efficiency, reduce cost, and help with quality assurance at each stage of your workflow.
Smartling is the leader in a world where AI-led translation is the solution to millions of businesses’ product and marketing needs.
Get accurate translations in seconds with zero complex configurations. Watch our short, 5-minute demo to learn more.