Artificial Neural Network is Revolutionizing The Future of the Translation Industry

Do you know that a full-time working translator can translate approximately 520,000 words per year?

There would be no wrong in saying that the translation industry has existed for centuries and will progress in double digits in the upcoming years. Because digital realms continuously push for more shared and globalized experiences, the current worth of the global translation industry is $56.1 billion, and the figure is expected to increase at a swift pace in upcoming years. The number is projected to surpass $70 billion by the year 2023.

It’s been more than 10 years since the launch of Google translate by utilizing phase-based machine translation algorithms. As the technological advancements never dig into the past, AI and ML-powered image recognition and voice recognition capabilities continue to redefine how this globe trades. It is getting even more challenging to enhance machine translation capabilities with every passing day since there is still a long journey to cover.

Presently, AI-powered neural machine translation is very high in demand in the global translation market because it can be directly trained on the source as well as target text and does not require a pipeline of standardized systems like statistical machine learning.

The encoder-decoder attention model architecture in neural machine translation engines arranges sentence-like lengths to be utilized as inputs to the model and does the translation with an accuracy rate of 60% to 90%

Let’s dig deep about how artificial neural networks are reshaping the dimensions of the translation industry.  

How AI is Demolishing the Language Barrier

When it comes to translating speeches and texts, artificial intelligence overcomes one of the ginormous barriers among humans: language.

From Facebook feeds to browsing international pages on Google, cyberspace is surrounded by AI translation. Innovative artificial intelligence algorithms permit instant translation across numerous mediums and are capable of handling an enormous amount of data that needs to be translated. 

Recently Microsoft has deployed its Translator application, which is so efficient that it does translate not just text but also street signs, images, and speech. The biggest breakthrough of Microsoft with this application is that the Translator also works without an internet connection. This application provides tremendous real-world benefits for travelers who travel to areas with limited connectivity to the internet.

Humans vs. Translators

You are completely wrong if you think that human translators will be replaced by NLP-powered translators shortly because that’s not going to happen. Artificial intelligence is still very far away from being capable of doing efficient and accurate multitasking. According to an AI-powered translation platform for professionals, TranslateFX, artificial intelligence will not replace human translators with AI software in the upcoming years. Artificial intelligence will make humans more productive and efficient in their jobs soon.   

AI-powered software can enhance the translation of complex legal documents such as contracts, disclaimers, press releases, confidential agreements, research reports, business plans, prospectuses, licenses, financial reports, corporate announcements, terms, and conditions, enabling businesses to negotiate comprehensively and effortlessly.

To cut a long story short, NLP solutions powered by artificial intelligence will elevate human intelligence into complicated document translation.  

Augmenting Human Intelligence

The accuracy rate of neural machine translation improves with the enhancement of computation power, neural network architecture, and data quality. This practical conversion will attribute human beings to cherish the advantages of technological innovations and focus on what they are good at. Neural machine translation can be deployed for the instant, accurate production of the first draft.

The human brain’s subsequent work will be to augment the translation quality. This involves reviewing or post-editing for content mapping and accuracy of the machine-translated text. 

A vast range of translation tools residing in the market is extremely generic. From restaurant menus to storyboards, from chats to news, those translation tools are trained for the translation and assortment of a wide range of content. Machine translation engines cannot translate text accurately and efficiently without understanding text utilization, targeted audience, and circumstances.  

What Does the Future Hold?

Considering the advent of cutting-edge technology, machine learning engines will provide more customization in the upcoming years to fulfill the requirements of individual industries and enterprises.

Custom machine translation engines will be designed for certain enterprise documents, including brochures, reports, and case studies targeting a particular business audience. Custom machine translation engines can enhance the accuracy rate to the extent of more than 20 percent of the translated text. 

Consistency will be the bone of postulation in the coming time, an ambiguity that is addressed with additional natural language processing along with machine learning algorithms developed as per the context.

Also, augmented human intelligence still has a long journey to cover in the translation industry. Hence the economies will be brought together in the upcoming years with the power of Neuro-Linguistic Programming (NLP) in the translation industry. Also, it is proved from all of the above-mentioned facts that artificial intelligence plays a promising role and will prove beneficial in enhancing the accuracy and efficiency rate of translators more in upcoming years.