Hackernoon logoWays To Overcome Linguistic Barriers with Language Technologies by@evan4morris

Ways To Overcome Linguistic Barriers with Language Technologies

Big data and machine translation technologies have enabled the world to do business as usual. Big data is now being utilized in every other industry - one way or the other. Big tech companies like Facebook, Google, Apple, Microsoft are also leveraging neural network methodologies to translate content. Public authorities are using similar solutions to communicate with the migrants in their countries who don’t speak their primary language. The tech companies are also cooperating with the governments to limit the spread of COVID-19.
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@evan4morrisEvan Morris

Known for his boundless energy and enthusiasm. Evan works as a Freelance Networking Analyst, an avid

COVID-19 has impacted every other industry and has made people adopt newer norms. The traditional translation industry is no different. Several disruptions have been introduced to keep things moving, thanks to Big data and machine translation technologies that have enabled the world to do business as usual.

The impact, applications, and scope of Big Data have got bigger and wider day by day. It is now being utilized in every other industry - one way or the other. For example, the media and entertainment industry is utilizing predictive analytics quite well to derive useful insights to create engaging, impactful content, and improve consumers’ experiences. In terms of generating data, the banking and financial industry is at the top as the amount of data they generate every second will grow by 700% this year. Imagine if 100% of this data was used - how frictionless banking and financial transactions would be.

That said, big data for the translation industry is an entirely new phenomenon that has been made possible with the presence of cloud-based translation platforms and machine translation neural technology. Businesses that were earlier using the traditional brick-and-mortar model have shifted to digital mediums. Further, there are several use cases where a combination of neural networks and big data is being used to enable translation to regional local languages.

A Language translator for business

In this era and unprecedented times, when ecommerce is the only thriving model, every other business aims to transform its business model and go live. However, the key impediment to their entry into the digital world is language. Do you know that of all the internet users around the planet only one-third know English and the rest are regional language users?

What could this possibly mean? 98% of the potential online customers can only be tapped if content in the English language is translated to 48 other well-known languages spoken around the world. That’s where translation services prove to be quite impactful. The large quantum of translation requirements is mostly met through big data and machine translation (multilingual neural) technologies.

In fact, big tech companies like Facebook, Google, Apple, Microsoft are also leveraging neural network methodologies to translate content. These companies are using Big Data to crunch words and make machine translations as accurate as possible. They are even making sure to get the cultural context right for precise communication.

Pocket translators for logistics

Since the entire world is intricately connected, it’s quite impossible to stop the movement of people and goods from one country to another. To make traveling safer for all the passengers, airport authorities are using hand-held voice-interpreters powered by machine translation (neural network) to translate and communicate about travel histories more effectively and clearly.

Public authorities are using similar solutions to communicate with the migrants in their countries who don’t speak their primary language. For example, the Australian Government has sponsored a national translation program at their national borders to facilitate migrants by communicating important information in their native languages. Currently, they are using combined solutions of human interpreters and machine translations.

On the other side of the world, in the USA, minorities like Hispanic people are suffering disproportionately because of the language barriers between healthcare and front liner workers. Around 34% of New York's population is Hispanic to which the public authorities found a creative solution of using video conferencing for translation services.

Even before the COVID pandemic hit us, a machine translation initiative named Gamayun was taken by an NGO called TWB - Translators without Borders in collaboration with CISCO. This initiative was aimed to help people who speak minority and marginalized languages. Because of artificial intelligence and big data, this program is estimated to scale up to 10 marginalized languages over the period of 5 years, according to a CISCO representative.

Tracking threats using machine translation

Public health authorities are also using content online to track the spread of COVID-19. Countries like Israel, China, South Korea have already used some or all of such data. The tech companies are also cooperating with the governments to limit the spread of this deadly virus. Uninterpreted data combined with machine translation is being used to track potential virus carriers. For example, the Israeli government is using machine translation on social media platforms that enable them to convert all the Arabic content into Hebrew which makes it easier for them to track people carrying this virus.

Because of the high-pressure and critical situation, the way big data and machine translation is being used might not be up to the standards. The data can prove to be quite noisy with duplicate and unnecessary data and it’s also quite possible that the quality of the data collected might be sub-optimal.

On the flip side

While technologies like machine translations help overcome the barriers and are being used for the right purposes, it has also generated privacy concerns. Currently, the usage of such information is for the benefit of the citizens but it could also turn into a deadly weapon in the near future, especially in the case of countries with political unrest. Therefore, the right policies and legislation need to be in place to support the usage of these technologies and avoid privacy concerns.

Evan Morris Hacker Noon profile picture
by Evan Morris @evan4morris. Known for his boundless energy and enthusiasm. Evan works as a Freelance Networking Analyst, an avidRead my stories

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