What is Language Translation?

A global market has incentivized many companies to try to bridge the linguistic barrier. Organizations that operate globally or are looking to do business overseas rely on language translation, and, especially in the case of conversations and documents, accuracy is crucial.

Understanding Language Translation

While language translation may seem straightforward, languages – and the ways they are spoken by individuals in various places, communities and contexts – contain complexities and nuances that can complicate the process. Translation errors and ambiguities can be embarrassing and potentially cause offense, so businesses are investing in high-quality translations.

How AI is Used in Language Translation

Simple machine translation often substitutes words in one language for another, causing confusing or incorrect interpretations as not all words have a direct equivalent, and many words can have multiple meanings. AI transforms this process with Machine Learning (ML), moving beyond simple word-by-word translations by understanding and considering tone of voice, phrasing, subject matter domain, cultural context, use of slang and variations in sentence structure.

Types of Language Translation

Language translation, with the introduction of technologies, has developed and improved. Here are some of the different types of language translation you might use.

Human Translation

Human translation is, as suggested by its name, completed entirely by people. It is the oldest form of translation. Humans can spot idioms, grammar and context, which machines usually struggle with, but can be very resource-draining and time-consuming.

Machine Translation

If a translation is completed by a device without human input, it is considered a machine translation. Machine translation has evolved during the past few years from simple word-by-word translation to more sophisticated AI models. One of the biggest advantages of machine translation over human translation is speed.

Hybrid Translation

Hybrid translation uses both machine and human translation. This is the best of both worlds: it takes advantage of the speed, scale and low cost of machine translation, while using humans to clean up any errors or language ambiguities that machine translation may have missed.

Interpretation

Interpretation is the translation of spoken language in real-time, as you might see in a global conference or a business meeting where the parts do not speak the same language. The fact that interpretation happens simultaneously or immediately after the original speech means that there isn’t the same time for review (or often research) that might accompany the translation of a document.

Pros for Using AI Language Translation

AI language translation has greater capabilities, giving it certain benefits over human translation.

Speed

AI language translation can speed up the process in many ways. If used by itself, it can handle much larger texts more quickly and in a wider variety of languages than a human translator. If used in conjunction with human translators, it can provide a first draft to be just checked for accuracy. Real-time translation of text messaging exists today, and real-time translation of voice in conversation is right around the corner.

Efficiency

The improved understanding of AI in language translation means there is less need for post-translation editing by human translators. This makes the process more efficient, as less human intervention means a suitable and accurate translation can be reached more quickly.

Improved Accessibility

AI translation can handle a wide variety of languages, meaning that businesses can reach wider audiences and accommodate more people. This is especially important if you want to future proof your content, and be able to operate in multiple countries with different languages.

Cons for Using AI Language Translation

Despite the benefits of AI language translation, languages have natural complexities that AI translation engines can struggle to handle.

Maintaining Meaning

While AI translation is an improvement on the traditional machine models, there are still a lot of nuances within languages that can be difficult to pick up. AI translation may provide an accurate translation of the words within a text, but it is likely to not be able to pick up on humor or sarcasm, for example, so the meaning behind the words could become lost as it fails to understand or detect what a text is really trying to say. AI language tools struggle to deliver accurate translations that fully account for subject matter domain and cultural context. But such tools do exist, like Sutherland Translate AI^TM.

Difficulty Detecting Cultural Differences

As AI language translation may struggle to maintain the meaning of texts, cultural differences can also be lost from the original text to the translation. AI translation engines don’t have the deep cultural knowledge that can be important to translations. This can lead to potentially misleading or even offensive translations. Very few translation tools are effective as Sutherland Translate AI^TM is accounting for cultural context in translation.

Accuracy and Consistency

AI language translation still isn’t at a place where it can be relied upon to provide entirely accurate translations. While it has reduced the need for post-translation editing, it would be unwise to not review and edit translations, particularly for sensitive or high-impact content.

Implementing AI Language Translation

Before implementing AI into your language translation processes, it’s important to think about what content you wish to translate and what an appropriate process for translating this content would look like. Unambiguous content may be able to rely entirely on AI translation. But as content becomes more sensitive, from product titles to press releases, you may want to think about the benefits of establishing a degree of human intervention.

If possible, training your chosen machine translation engine with your own data can be highly beneficial. This means you can ensure your machine translation engine is using high-quality, relevant data with augmented knowledge intelligence. It’s also important to run tests before blindly trusting your AI language translations. This includes running tests in multiple languages, as some may be stronger than others.

Advancements in Machine Translation Technology

Machine translation has come a long way from its origins with the integration of AI. Neural machine translation (NMT) is a development in machine translation that harnesses AI and neural networks to analyze patterns in language and generate more accurate translations. NMT continues to improve as ML works to train and improve the results from NMT engines.

The Future of AI and Language Translation

It’s more possible than ever before to reach and connect with a wider audience. As businesses grow their reach across the globe, it’s increasingly important to have correct and relevant translations at a lower cost, raising the demand for reliable AI translation. However, Human translation is still superior to AI language translation in its ability to understand nuances like context and idioms, so AI is not set to replace human translation entirely for the foreseeable future.

About Sutherland Translate AI^TM

Sutherland Translate AI^TM is an AI-enabled translation platform that empowers your contact centers. Sutherland Translate AI^TM uses AI and ML with the top translation engines to supply your employees with trustworthy translations. The platform captures customer messages or queries across various platforms and translates them into the agent’s native language.

Sutherland Translate AI^TM provides you with:

•   A strategic advantage.
•   Advisor productivity.
•   CX metric improvement.
•   Speed to market and scale.

Discover more about Sutherland’s Knowledge Management Services:

•   Case Study: New AI-Driven Language Translation Tool Lets Spotify Grow Its Service Capabilities and Customer Engagement
•   Blog: Customer Care Super Agents: Meet the New Value Creators
•   Blog: AI, Chatbots, Cybersecurity, the Digital Workplace and 2022