In an age of intensifying globalization, more businesses than ever are looking to overcome language barriers to facilitate expansion efforts. Cultural and language barriers can be difficult challenges to overcome, especially because they affect every aspect of a business’s communications, including B2B communications, as well as customer support teams dealing with queries from every corner of the globe.
Thankfully, artificial intelligence is reshaping the way businesses operate on the world stage. Nowadays, the best AI-powered solutions can help automate time-consuming translations and localizations, while also making everyday communications easier.
Nowadays, it’s becoming easier for international businesses to overcome language barriers. AI now takes care of complicated tasks that were once the sole responsibility of human linguists. Machine learning, a specific type of AI, now makes it possible for computers to make more informed decisions and apply self-learning principles to these decisions.
AI machines are used across many industries, including the financial sector for forecasting and the retail sector for sales and marketing purposes. AI and machine learning provide previously unavailable insights, handling queries in just about any language simultaneously.
Advancements in machine learning also make it possible for AI to offer more refined responses to a search query. Examples of language barriers that once caused an issue for search include non-native English speakers using misspelled terms. Nowadays, AI is incredibly proficient at recognizing intent and context. In other words, a misspelled search term isn’t going to stop a user from getting to where they need to be.
AI is evolving rapidly, but it still needs a helping hand from humans. AI translation systems depend on human users to provide them with contextual meaning and introduce them to natural language and new vocabulary. This is often referred to as AI enablement.
The more an AI-powered translation system is used, the better it gets at translating texts from one language into another. If it suggests an incorrect word and an amendment is made, this correction will be saved for future reference. This makes it easier to automate translations, without sacrificing too much in the way of nuance and context.
There are more than 7,000 spoken languages in the world. Although 3,000 of these are so-called low-resource languages that rely on the spoken world alone, the rest all have their own writing systems.
Although these codified languages are much easier to translate in theory, automatic translation can’t be readily applied to most of them. Google Translate and Microsoft Translator each support around 100 languages, while DeepL supports translations in around 30 languages.
While common language pairs like English and Spanish are widely supported, low-resource languages aren’t as easy to come by. However, AI is making bridging the language gap between commonly spoken and low-resource ones a very real possibility.
A key element of AI and machine learning is natural language processing (NLP). In short, it allows translation machines to more accurately comprehend languages. It’s thanks to NLP that machine translation is possible. It can carry out simple tasks like proofing translated texts for spelling and grammatical errors. It can also understand some of the nuances of human languages, such as sentiment and emotive meaning.
NLP uses advanced algorithms to not only translate raw text but also predict purpose and intent. It can provide suggestions and insights, along with basic text-to-text translations.
Currently, human linguists still need to refine translations delivered by NLP, but it’s a fast-evolving field that can already help automate the fast translation process.
The most advanced AI uses neural network technology to power translations. Neural network technology can imitate human thought processing, making it easier for AI to grasp the contextual meaning of sentences, as well as individual words.
It’s a fairly simple concept. However, the big hurdle here is minimizing the amount of data a neural network needs to provide reliable results.
Modern-day neural networks can be trained to identify and comprehend basic sentence structure and general language features. This makes it possible for linguists to access low-resource languages. Once neural networks have been pre-trained, they can be left to their own devices to provide automated translations, without requiring the input of bilingual data.
A human only requires a fraction of the raw data that a machine engine does to learn a new language. Typically, humans begin with generalized study to comprehend a new language, before slowly developing a workable vocabulary.
By contrast, machines need vast amounts of data before they deliver even basic translations. The ultimate aim is to develop AI machines that require comparable amounts of information as humans to deliver reliable translations consistently.
Online marketplaces and e-commerce platforms have taken advantage of AI-powered machine translation. Take eBay Machine Translation (eMT) as an example. This machine learning system provides near-instant translations between languages for eBay users.
This in-house system quickly proved more reliable than the external services eBay was previously using. In fact, the introduction of eMT coincided with a 17-20% upswing in exports to Latin American countries.
AI-powered translations are becoming more proficient than ever before. However, there’s still a way to go before they’ll replace human linguists entirely. No matter how automated your translation process has become thanks to AI-powered solutions, you’ll also need experienced translators to take charge of post-editing to ensure your localization efforts are on the right track.
At BLEND, we offer a full slate of professional localization services, including translations, post-editing, multilingual voice-over recording, and subtitling services. With thousands of experienced linguists in our network working in more than 120 languages, we can help you penetrate new markets with ease. Want to learn more? Get in touch with the team today.
As BLEND’s Localization Solutions Engineer, Fouad is a seasoned expert in translation technologies, including TMS, CAT tools, AI and MT. With over 14 years of industry experience, Fouad ensures our clients receive the best and most efficient localization processes.
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