What Does the Post-Language Economy Look Like

This article was originally published on Inc. What Does the Post-Language Economy Look Like.

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How translation technology is changing the face of small business on a global scale.

The greatest barrier to global trade is not space and time, or even geopolitics. The greatest barrier today is language. Only major corporations have been able to set up mirror offices and global operations networks to facilitate international trade. Human translators, an expensive resource, act as bridges between producers and consumers or business partners who speak different languages. But this is an imperfect solution to a significant challenge. Very few people are fluent, or even competent, in more than a handful of languages, making it difficult for companies to do business in more than a handful of countries.

Much of the world’s economy is comprised of small businesses that do not have the resources to overcome dozens of language barriers in countries all over the world. But if small businesses could overcome the language barrier, what would the global market look like? Where would we be if the ‘mom and pop’ stores that fuel our local economies were able to join the global market?

“There is a wealth of potential in start-ups and entrepreneurial businesses all around the world,” says Denis Gachot, CEO of Systran Group. “One of the biggest obstacles to harnessing that potential is the language barrier. Neural Machine Translation (NMT) is working to bring that wall down.”

Neural Machine Translation

A natural step in the progression of communication technologies, NMT is a tool that connects people who would otherwise have no means to understand one another. The technology is aimed at translating large volumes of business communications almost instantly and with more effectiveness than human operators.

Unlike preceding translation technologies, NMT builds a neural center of information that can be tuned for more apt translations. The network approach sidesteps the bottleneck often seen in translation technology that hinders the improvement of encoder-decoder systems. This “soft-alignment” is a reflection of our own intuition, so these language translations done by a machine are more human than ever. “This technology is of a caliber that deserves the attention of everyone in the field,” says Gachot. “It can translate at near-human levels of accuracy and can translate massive volumes of information exponentially faster than we can operate.”

NMT is an end-to-end learning system, so it learns and corrects itself through continued use. Picking up patterns in languages for more accurate translations, NMT systems will continue to improve with time and application, making them the ideal employee.

But part of the beauty of this system is that it is a scalable technology and capable of processing volumes of information exponentially faster than humans are able to. This makes NMT an affordable option for small businesses looking to take their products into more markets. Doors previously closed because of the language barrier are now swinging open. And the world is changing for it.

Companies Using NMT as Plugin

The last year has seen huge leaps in NMT technology. While it remains a tool predominantly for larger businesses, NMT is proving its salt as a revolutionary force in the international market. In September, Google researchers announced their version for this technology, which translates entire sentences instead of just single words, providing a more authentic and relevant translation. Currently, it functions in eight major world languages, able to service some 35 percent of the earth’s population.

Already, NMT is being used in clouds and network plugins. Facebook announced in March of last year that they would be using neural networks for their own page translations.

But most exciting in this progression of NMT is its ability to change the way small businesses have been able to contribute to the global market. Google and Systran are racing to roll out NMT in new languages, already delivering dozens of language pairs. The linguistic technology now facilitates communication in 130 different languages, providing real solutions for internal collaboration, online customer support and eDiscovery in multilingual contexts.

What this means practically is that an online store owner in St. Petersburg, Russia is now able to reach a customer in Montevideo, Uruguay and market and discuss her product with reliable translation technology as the go-between.

Economic Outcomes

Small businesses are key to economic strength. Properly equipped with tools and resources, they have the power to grow and shape economies at any scale. Smarter regulations and tax structures are not the only factors at play here. These businesses need to be able to pursue consumers wherever they may be.

According to the U.S. Small Business Administration (SBA), 99.7 percent of all employer firms are small businesses. They have generated 64 percent of new jobs, and paid 44 percent of the total United States private payroll in the last 20 years. The prospect of enabling these small businesses to broaden their customer base and compete in the global market is more than exciting; it is world-changing.

Gachot adds, “For many years, we have tried to deal with language as if it was a barrier for communication – while with neural machine translation, language difference is what makes the richness of communication between different cultures.”

NMT looks to be the pivoting step for global trade. With the language wall crumbling, more small businesses will be able to bring their unique, quality-crafted products and services onto the international market scene, which is good for everyone.

SYSTRAN’s team is setting private meetings for an exclusive view of the PNMT concept. For more information, contact Craig Stern at craig.stern@systrangroup.com and to set up a meeting, click here.

Related Links

SYSTRAN PNMT DEMO

Positive Feedback from PNMT Beta Tester

This article was originally published on Inc. What Does the Post-Language Economy Look Like.

How Neural Machine Translation Will Change E-Discovery

When a global enterprise gets sued, it’s vital to know who is involved and how. But finding out who to blame isn’t always simple.

Global law firms are tasked with sifting through thousands, sometimes millions of emails, chats, and legal documentation during eDiscovery. These documents and audio recordings could be in many different languages and stored around the world. Sometimes that data is stored in countries with strong data protection regulations, such as Brazil and parts of the EU, so it cannot under any circumstances leave the country.

So, how can an office in the U.S. review hundreds of days of correspondence in multiple languages?

If the firm hires translators, they’ll need dozens with a strong knowledge of everything from slang to deep subject matter expertise of the topic in discovery. If instead they decide to go with an e-discovery translation solution, they’ll still need help during the review process, especially for data in Asian languages – there are several ways to interpret one word, for which there may be five slang alternatives. In either case, the team must spend a lot of time and money to get reliable and accurate results.

Until now, that is.

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SYSTRAN to Showcase Neural Machine Translation Technology at InnoXcell

This article was originally published on PR Newswire SYSTRAN to Showcase Neural Machine Translation Technology at InnoXcell

20161206_125742SYSTRAN, a global leader in language translation technology, showcased its newest translation software, called Pure Neural Machine Translation (PNMT), at the InnoXcell Annual Symposium focused on China-U.S. regulatory compliance and eDiscovery in New York City this month.
As an exhibitor and sponsor of the event, SYSTRAN’s team provided attendees an exclusive view of the PNMT concept and how it can be utilized by the legal and regulatory compliance industries to boost productivity and cut translation costs.

“Neural Machine Translation ushers in a new era for Language Productivity Tools, making MT a genuine alternative to human translation,” says Ken Behan, Vice President of Sales and Marketing of SYSTRAN. “InnoXcell attendees will have a great opportunity to increase linguistic productivity in the GRC and eDiscovery world with this technology.”20161206_102527

Unlike statistical (SMT) or rule-based (RMT) translation engines, NMT engines process an entire sentence, paragraph or document taking into context the topic being discussed. The NMT engine models the whole process of machine translation through a unique artificial neural network, working similar to a human brain. The entire chain is processed end-to-end with no intermediate stages between the source sentence and the target, providing for more accurate translations.

 

As the legal industry increasingly works with multilingual content, such as emails from global companies, firms need a way to translate content quickly, reliably and cost-effectively. SYSTRAN’s software driven by machine translation provides organizations the ability to automatically translate audio and text in more than 130 different language pairs. The software can also be leveraged to perform real-time translation on intranets and other tools. At any given moment, users can translate entire sites, blogs or document to find and understand foreign-language info in real-time.

20161206_163917The InnoXcell conference took place in New York, NY on December 6. Attendees were able to learn more about the PNMT concept, how it works and what it will allow companies to do. To set up a meeting or schedule a demo, contact Craig Stern at craig.stern@systrangroup.com.

About SYSTRAN

For over 48 years, SYSTRAN transformed the way global organizations such as Apple, Adobe, Daimler, HSBC, and Symantec meet the challenges of communicating globally via advanced machine-based translation technology. With the ability to facilitate communication in over 130 languages and 20 vertical domains, SYSTRAN enables instantaneous and automatic multilingual translations for texts, emails, chat, web pages, mobile apps, documents, user-generated content and more.

For more on SYSTRAN visit www.systrangroup.com

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SYSTRAN is far along the NMT path

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SYSTRAN announces the launch of its “Purely Neural MT” engine, a revolution for the machine translation market

 

This article was originally published on PR Newswire SYSTRAN to Showcase Neural Machine Translation Technology at InnoXcell

SYSTRAN to Present on Neural Machine Translation at Association for Machine Translation in America Conference

This article was originally published on PR Newswire SYSTRAN to Present on Neural Machine Translation at Association for Machine Translation in America Conference

SYSTRAN, a global leader in language translation technology, presented at the Association for Machine Translation in America (AMTA) conference in Austin this month. The talk, titled "Building Renewable Language Assets in Government Domains," included insights from the company's latest efforts in Neural Machine Translation.

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The presentation, given by Beth Flaherty, SYSTRAN's Director of Government Solutions, and Joshua Johanson, a computational linguist with SYSTRAN, discussed the company's work in specific domains and languages of interest to the government.

"SYSTRAN welcomes this opportunity to share our accomplishments to date with the government community," says Flaherty. "We will also reveal some of our plans to integrate neural network technology into our offerings to further serve the public sector with faster, smarter machine translation."

As demand for multilingual content continues to increase, public-sector organizations struggle to produce content efficiently, reliably and cost-effectively. SYSTRAN's software driven by machine translation provides organizations the ability to automatically translate audio and text in more than 130 different language pairs. The software can also be leveraged to perform real-time translation on intranets and other tools. At any given moment, users can translate entire sites, blogs or document to find and understand foreign language information in real-time.

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The AMTA conference took place in Austin, TX from October 28 through November 1. SYSTRAN's presentation was scheduled for October 31 from 5 – 5:30 p.m. on the Government track. The company also exhibited at the Technology showcase on October 30 from 12:30 – 3:30 p.m.

To learn more about SYSTRAN and its machine translation technology, visit http://www.systrangroup.com/.

This article was originally published on PR Newswire SYSTRAN to Present on Neural Machine Translation at Association for Machine Translation in America Conference

We are SYSTRAN and we love languages…

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We are SYSTRAN. We love languages, lots of languages. We are a human-sized company but we have linguists for almost all of the 140 language pairs we support.  That’s a big number, but don’t be misled- some of us are fluent in many languages. Nevertheless, we love languages and we don’t believe in the one-fits-all technology regarding language processing.

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