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  1. DZone
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  4. How Are Smart Technologies Changing the Translation Industry?

How Are Smart Technologies Changing the Translation Industry?

Discover the role of technologies in automating translations and providing higher accuracy without human interaction and the future of translation.

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Anahit Ghazaryan user avatar
Anahit Ghazaryan
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Aug. 17, 22 · Opinion
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We are currently at a point in language and technological development when a collision is inevitable – some may even argue that it has already occurred. We are simply waiting for the dust to settle. Digitalization, the Internet of Things, AI and machine learning, and – going back even farther – the smartphone, voice recognition, and the introduction of the internet and social media; all those technologies have contributed to the world we live in now. 

Of all technologies, Artificial Intelligence is the most spoken one that is already used in every industry. Today, we will talk about the translation industry undergoing dramatic changes. Businesses and communications not limited to physical borders are now working on erasing language barriers. While Machine Translation (MT) has been around for a long time, the current usage of Artificial Intelligence has dramatically enhanced the availability of real-time, at-your-fingertips translation to the general public like never before. AI provides various benefits, including the capacity to incorporate context and language specifics with improved accuracy. 

Whether you are involved in the translation industry and technologies, it may be quite an exciting read. Let us begin with a fundamental question: What happens when two things, for example, language services and technology clash? We get real-time translation technology.

Translation Industry Predictions

The expansion of language translation is significantly driven by smart technology development and penetration into translation. Indeed, the translation sector, valued at $39.37 billion in 2020, is projected to reach 46.22 billion by 2028. Aside from this data, introducing technical translation engines and shifting to machine translation has been a true revolution in the translation segment. Thus, in 2019, the amount of translations performed by machine translation engines has already overtaken that of professional human translators globally.

What Is Real-Time Translation Technology? 

Real-time translation technology (RTT), as the name suggests, refers to a tech-driven solution that enables instant translation of any type of content from one language to another. You read it right, any kind of content, because today, technologies help translate not only text; you can have voice translation, object detection, translation, image translation, etc. Used both for personal purposes and at the enterprise level, RTT improves communication and covers the language gap. 

For corporate purposes, translation providers offer API integration in services covering inner processes and customer communication like CMS management, customer support, etc.

Developed to support human translators, machine translation software solutions are quite intelligent now to provide specific translations without much editing. The technology standing behind modern real-time translation software programs is the latest neural machine translation (NMT). Machine learning algorithms and pattern recognition software identify words and sounds, but neural networks and deep learning systems evaluate a speech in context and phrases. Following that, the data is encoded and translated. RTT tools with high processing power have access to a database of words extracted from millions of pages. The complete procedure now takes around 2 to 5 seconds with an accuracy of 85%. 

The Role of AI in Translation: And How Does It Work?

Many technical developments, most notably language translation, rely heavily on voice interactions. In this case, AI provides immediate translation across various formats, including text, audio, graphics, and even street signs. AI can now manage massive quantities of text or speech that require translation. 

Artificial Intelligence, based on artificially produced neural networks, translates entire phrases rather than individual words, taking into account word relationships of the language for more accurate translation. With neural machine translation (NMT), AI can learn from previously completed translations, picking up on word use, phrase structure, and purpose depending on context. This approach is far more successful than any previously utilized technique since it uses less memory and data to work properly. All translations are linked, providing superior context and accuracy to large volumes of voice or text.

Behind the scenes, AI is supported by natural language processing, image recognition, prediction engines, and recommendation. Any piece of translation, be it a word or a text, goes through the following stages;

Data collection - comes from a number of places to the AI stack.

Data storage - quickly accessed storage for Big Data, often cloud technology.

Data processing and analytics involve machine learning, deep learning, natural language processing, sentiment analytics, image recognition, and recommendation engines. Algorithms in the form of services are accessed through third-party APIs.

Data output and reporting - depending on your needs, the output can be in different forms like voice cloning and translation of the speech, text form, etc. 

How Do Technologies (AI & NLP) Help Human Translation?

The implementation of AI in language translation brings nothing but benefits to human translators, businesses, and anyone looking for faster and easier translation tools. 

Continuous Improvement

AI-powered neural machine translation continually learns and develops with human feedback utilizing previous translations or linguistic assets. It means the more you use the translation tool, the smarter it gets, and the more accurate the outcome is. 

Specific Vocabulary for Different Needs

With a terminology database included in the stack of advanced AI editors, it is possible to handle terminology more efficiently by arranging terms with customized meta-data. You can import terminology using meta fields or create new fields to improve translation concordance. This advantage is critical in technical translations and specialized content.

Time and Cost-Efficient

If you don’t require 100% accurate translation of large-scale documentation, machine translation is the thing to leverage. AI-driven translation improves and learns, and the process of machine translation post-editing gets easier, reducing the costs and time required by human translators. As a result, organizations with limited resources may also deliver a tailored worldwide experience.

Will AI Replace, Human Translators? 

The progress is unstoppable, and, in fact, no one wants to go back to times when information was inaccessible. One more question: Will AI replace humans in any industry, including translation? The short answer is “No.” 

No matter how smart and fast AI is, the technology does not have empathy, the thing we will always look for. Even with 99% accuracy, there is still 1% of human interaction that can make the translated content just perfect. What we can do is use technologies in our favor and make life more comfortable. 

AI Machine learning Translation

Published at DZone with permission of Anahit Ghazaryan. See the original article here.

Opinions expressed by DZone contributors are their own.

Related

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  • Transforming Translation: The Power of Context in NLP
  • The Only AI Test That Still Humbles Every Machine on Earth
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