What Does the Post-Language Economy Look Like

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

CREDIT: Getty Images

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.

This Translation Software Giant Is Empowering Today’s Top Global Companies

This article was originally published on Forbes This Translation Software Giant Is Empowering Today’s Top Global Companies.

 

Since launching in 2006, Google Translate has grown to over 500 million users worldwide, translating more than 100 billion words daily. In 2016, the tool supported 103 languages, with 92% of its users residing outside of the United States.

While the tech giant sits comfortably atop the growing list of translator apps, there’s one longstanding giant in the shadows, actively innovating and developing the blueprint for how companies like Google define the future of global communications.

Founded in 1968, SYSTRAN stands as the leading provider of language translation software products, delivering real-time language solutions compatible for desktop, mobile, and web-based platforms. Credited as a pioneer in machine translation for over four decades, SYSTRAN remains committed to advancing multilingual communications around the world, removing language barriers between people and businesses to make forging meaningful connections seamless.

SYSTRAN’s software facilitates communication in 140 language pairs, across 20 vertical domains, making them the most sought-after translation software provider amongst top-tier global companies and public agencies. Their translation software improves relevant searches, content management, customer support, B2B communications, and plays a pivotal role in scaling global e-commerce companies.

The tech company has developed a proprietary software product called Pure Neural Machine Translation (PNMT), which is an independently developed variation of a technology called Neural Machine Translation. Instead of translating one word at a time, the technology reads full sentences to determine the meaning and assure each translation is properly contextualized. Pure Neural Machine Translation has proven to be more effective than translation software and services used on Facebook or Google Translate.

Equipped with a trained and experienced team of engineers and linguists, SYSTRAN not only expects to compete, but looks to ultimately surpass power players like Google in the race to design a truly connected world without language divides.

I spoke with SYSTRAN CEO Denis Gachot about the vision behind his company, eliminating language barriers, and his plans for transforming how people and businesses communicate.

What was the specific void or opportunity that inspired the idea behind SYSTRAN’s PNMT?

Denis Gachot: In 1968, the United States Air Force called us to translate Russian to English during the Cold War. The stakes had never been higher; precision, security and speed were required to translate a high volume of data quickly. The only difference today is that we’re not just helping the intelligence community. Large corporations are in a battle, and have global teams that need to get languages right and uphold tight security.Thus, the void we needed to solve for was quality. Pure Neural Machine Translation (PNMT) has brought us translation quality that raised the standard, and is now measured by how well it sounds like a native speaker; a remarkable attribute for a machine to be judged on. PNMT is furthering the opportunity to allow people from anywhere in the world to be able to connect with anyone and understand anything.

What were some of the notable challenges you faced while developing your business?

Denis Gachot: One challenge is that most people are unaware of how they can apply machine translation to their business. Imagine an auto manufacturer who would like translate 200,000 pages of product manuals for communication amongst teams in Germany, Columbia and Japan, using email and instant messaging. They would have two translation engines: One that is optimized for the manuals, and another that is optimized for colloquialism (casual speak and slang). Custom translation engines are created with domain specific dictionaries, customized vocabulary, and preferences. For example, if you have a manufacturing profile, the word ‘PIN’ is defined as a metal object. However, if you have a banking profile, the word ‘PIN’ is defined as a password. Further, you can customize vocabulary based on your company’s nomenclature. You can save settings such as ‘never translate your brand’s name’. Also, anything that’s been edited can be saved in the profile to optimize future translations.

Can you provide an example of a company that uses this form of machine translation and how it has benefited them?

Denis Gachot: Adobe, a company with over 100 products, is an example of how to leverage machine translation. They have detailed support FAQs and product education documents in dozens of languages. If they didn’t, phone lines would start to light up with customer service requests in Russian, Hebrew, Japanese, Chinese, and Spanish, because users can’t find support in their language. The applications are nearly limitless: translating patents from Chinese to English, helping law firms find evidence in hundreds of thousands of files in different languages, and translating scientific research, just to name a few.

Your company was founded in the 1960’s — How has both the language translation technology and the market for this technology evolved over the past several decades?

Denis Gachot: Language technology has advanced in line with technology and culture in general. In 1960, the average person spoke to five people a day. Today, you have over 2,000 friends and colleagues anywhere on Earth that can instantly message each other. We’re seeing our customers apply neural machine translation and big data to evolve everything: sales, e-learning, publishing, customer service, email, eDiscovery, compliance, big data manipulation, and mobile apps. Needs have evolved to fluency. With fluency, we now judge the translations based on how well the message captured the meaning, and how much it sounded like a native speaker; that’s phenomenal.

What goes into the process of developing translation technology and what other aspects of human communication or behavior must be studied in the process?

Denis Gachot: Technically speaking, it’s artificial intelligence. Like the human brain, the neural machine translator learns through a process in which the machine receives a series of stimuli over several weeks. Over the course of those few weeks, the process mimics ‘deep learning.’ Think of ‘if, then’ statements — that’s considered ‘shallow learning.’ Deep learning is multiple ‘if, then’ statements stacked. Our technology runs complex algorithms that keep the engine learning, generalizing the rules of a language from a given translated text, and producing a translation that is eerily close to one done by an actual human. The linguistic expertise (the understanding of language), is a more unique set of knowledge than the software coding, and our machines have been undergoing that process of learning for over 49 years. We’ve amassed such a knowledge base that most users think the translation is done by a human. The reason it is so good is because of the underlying study of how a human being uses language.

How do you see a company like SYSTRAN shaping how people from all parts of the world build connections with each other?

Denis Gachot: If two people can’t speak the same language, there is no connection. Dale Carnegie once said, ‘to understand someone is to repeat back to them what they said better than they originally described it.’ When you confide in your best friend, you do it because you feel heard. It transforms businesses, personal relationships, and even random encounters with strangers. In the future, we’d love to release devices that you can talk into and they translate instantly. Imagine having something as small as a lapel pin that gave you the ability to understand what is being said and respond in any language, this is the future that SYSTRAN will be a part of, and hopefully, in the process help enrich all our lives. Communication fosters connection. Neural Machine Translation fosters connection through sophisticated algorithms that not only translate, but provide fluency so people are understood.

While America is multicultural, people live in somewhat of a westernized bubble — How does a company like SYSTRAN help connect these international communities and enrich culture in nations like the U.S.?

Denis Gachot: To understand and gain command of a new language is to know how a different set of humans and cultures view life. Take the expression of love, time, and death. In America, the word ‘love’ is used abundantly. I ‘love’ these shoes, this house, this drink and so forth. In most other cultures, that word is held for special times with loved ones. This is the foundation of connecting. At a practical level, the difference between the U.S. and the Continents is that our country’s language is the global language, so most Americans don’t know another language or haven’t gotten to know another culture. How many people do you know that have studied a foreign language in college but forgot it all because they didn’t’ use it. Now, imagine being able to send an email in French, an instant message in Korean, and co-create a PowerPoint Presentation in Spanish? Language is like mixing primary colors to make new colors. In Miami, for example, they speak Spanglish. There is a subset of rules about when to use English and Spanish in the same conversation. It’s beautiful.

How do you see SYSTRAN evolving over the next 3-5 years and where do you see your company fitting in the future of where this technology is heading?

Denis Gachot: Most, if not all industry leaders will continue to deploy artificial intelligence in some way. We are a part of that revolution. I am at liberty to tell you that we’re already embedded in many of the leading companies’ internal applications, hardware, and proprietary communication tools. The spoken word is the next frontier, as people move away from communicating with electronic devices in their hands — typing, swiping, tapping — and use their voices instead. Everyday functions like typing will be replaced by dictation, and even human-machine conversation. We already talk with smart home assistants that turn on other devices, answer our questions, and send us alerts. Language translation is a key component of the future of technology.

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 Forbes This Translation Software Giant Is Empowering Today’s Top Global Companies.

Managing Compliance Programs in Multiple Languages

Regulatory compliance is expensive, but the cost of compliance related failure is much higher. The top US banks paid out fines amounting to $204 billion in 175 settlements dating back to 2009*. It is challenging for banks and financial institutions to adapt to the complexities of regulations in a global marketplace. Policies need to support the modern pace of transactions and international trade. Therefore, compliance professionals and the tools they use have an increasing need to make sense of communications or data in foreign languages.

Current software platforms address the need to understand, analyze, and review archived communications proficiently in English. However, a critical subset of that content happens in foreign languages that most of the existing platforms do not handle. The key to ensuring compliance of data in foreign languages is being able to perform
real-time translations at scale, either as a stand-alone capability or an integrated function of the review platform. No textual data – no matter its language – is left out of the monitoring or review processes.

In the world of risk management, the focus areas below are becoming increasingly multilingual and require a consistent effort to ensure sustained compliance:

  • Trading communications and conduct
  • BSA/AML Programs
  • Insider leaks, business conduct, and HR issues
  • Corporate social media policy

REAL-TIME MACHINE TRANSLATIONS FOR RISK ASSESSMENT PROCESSES

SYSTRAN’s real-time translation supports multilingual data compliance with class leading performance in data centers and enterprise networks around the globe. The incremental capabilities and gains include:

  • Automated or on-demand machine translation (MT)
    of the messages for review, audit, or discovery processes
  • Identify the foreign languages in messages at volume and scale
  • Store translated files for audit or review cycles
  • Increase productivity and optimize cost simultaneously with MT technology in comparison to acquiring human translation resources
  • Streamline workflows by eliminating deviations to ad-hoc processes just to discover content in other languages
  • Increase workflow efficiency by integrating MT capability into the workflow that is designed for one language

SYSTRAN, a global leader in language translation technology, will showcase its newest translation software, Pure Neural Machine Translation, at FIBA AML compliance conference in Miami, FL, March 6-8.

For more information, contact Craig Stern at craig.stern@systrangroup.com and to set up a meeting, click here.

* source: Keefe, Bruyette & Woods (2015)

About SYSTRAN

SYSTRAN has been helping commercial, defense, and national security organizations capture mission-critical data for the last 49 years. We operate globally with locations in Americas, Europe, and Asia.

As the first software company to introduce Neural Machine Translation technology, SYSTRAN is continuing to lead the innovation in language technologies. SYSTRAN’s brand new Purely Neural Machine Translation (PNMT) products utilize Neural Networks and Deep Learning algorithms to achieve unprecedented translation quality that is near human translation levels.

Related Links

Positive Feedback from PNMT Beta Tester

SYSTRAN to Host Private Viewings of Pure Neural Machine Translation Technology at FIBA AML Compliance Conference

 

SYSTRAN to Host Private Viewings of Pure Neural Machine Translation Technology at FIBA AML Compliance Conference

This article was originally published on Newswire SYSTRAN to Host Private Viewings of Pure Neural Machine Translation Technology at FIBA AML Compliance Conference

 

SYSTRAN, a global leader in language translation technology, will showcase its newest translation software, Pure Neural Machine Translation, at FIBA AML compliance conference in Miami, FL, March 6-8.

Harvard partnered with SYSTRAN to develop the next generation of AI-based Language Translation that runs on Neural Networks. They call it Pure Neural Machine Translation (PNMT). SYSTRAN will sponsor FIBA AML to showcase how PNMT is helping companies solve the linguistic challenges related to multinational compliance and AML.

 

“PNMT is giving the banking industry a more powerful tool to maintain compliance, even when working with terabytes of data stored in multiple languages around the world,” says Ken Behan, Vice President of Sales and Marketing of SYSTRAN.

The PNMT engine is revolutionary in that it processes an entire sentence or paragraph in the context of the overall document topic, instead of translating segment by segment. This creates a far more accurate output than ever before seen with machine translation, especially for Asian languages. For compliance, accuracy in translation is important in being able to flag issues or suspicious transactions.

SYSTRAN’s software provides the ability to perform machine translation on both audio and text in 45+ language pairs.

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

To learn more about SYSTRAN’s machine translation solutions, visit https://demo pnmt.systran.net

Related Links

Positive Feedback from PNMT Beta Tester

This article was originally published on Newswire SYSTRAN to Host Private Viewings of Pure Neural Machine Translation Technology at FIBA AML Compliance Conference

SYSTRAN to Hold Private Viewings of Pure Neural Machine Translation Technology for eDiscovery Translation at Legaltech 2017

This article was originally published on PR Newswire SYSTRAN to Hold Private Viewings of Pure Neural Machine Translation Technology for eDiscovery Translation at Legaltech 2017

SYSTRAN, a global leader in language translation technology, will showcase its newest translation software, called Pure Neural Machine Translation (PNMT), at Legaltech in New York this month.

As the demand for multi-lingual litigation continues to increase, law firms need a way to translate eDiscovery data quickly, reliably and cost-effectively. PNMT is the perfect solution to this challenge.

“PNMT offers an incredible opportunity for legal firms to perform multi-lingual eDiscovery more efficiently,” says Ken Behan, Vice President of Sales and Marketing of SYSTRAN. “Having the ability to automatically translate terabytes of data and get reliable results is invaluable for law firms, especially when timelines and resources are tight.”

The PNMT engine is revolutionary in that it processes an entire sentence or paragraph in the context of the overall document topic, instead of translating segment by segment. This creates a far more accurate output than ever before seen with machine translation, especially for Asian languages.

In fact, early tests show that PNMT translated documents are of the same or even higher quality than human-translated content. Test subjects could not correctly identify which translated samples were done by machine translation versus a human. The quality is that good.

SYSTRAN’s software provides legal organizations the ability to perform eDiscovery translation on both audio and text in real-time in 45+ language pairs. The PNMT software can be used as a connector to eDiscovery software, such as Relativity, or on its own.

SYSTRAN’s team is setting private meetings for an exclusive view of the PNMT concept and how it can be utilized by legal teams to boost productivity and cut translation costs during eDiscovery. To set up a meeting or schedule a demo during Legaltech, contact Craig Stern at craig.stern@systrangroup.com

To learn more about SYSTRAN’s machine translation solutions for eDiscovery, visit http://www.systransoft.com/translation-products/integrations/cmless-for-relativity.

 

Related Links

How Neural Machine Translation Will Change E-Discovery

SYSTRAN for Relativity – More Information

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This article was originally published on PR Newswire SYSTRAN to Hold Private Viewings of Pure Neural Machine Translation Technology for eDiscovery Translation at Legaltech 2017

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’s Continuing Neural MT Evolution

by Kirti Vashee on eMpTy Pages, a blog about translation technology, localization and collaboration

Recently, I had the opportunity and kind invitation to attend the SYSTRAN community day event where many members of their product development, marketing, and management team gathered with major customers and partners.

The objective was to share information about the continuing evolution of their new Pure Neural MT (PNMT) technology,  share detailed PNMT output quality evaluation results, and provide initial customer user experience data with the new technology. Also, naturally such an event creates a more active and intense dialogue between company employees and customers and partners.  This, I think has substantial value for a company that seeks to align product offerings with its customer’s actual needs.

Ongoing Enhancements of the PNMT Product Offering

The event made it clear that SYSTRAN is well down the NMT path, possibly years ahead of other MT vendors, and provided a review of the current status of their rapidly evolving PNMT technology.

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Round-trip translation: no more entertainment with PNMT™ systems

Round-trip translation (RTT), also known as back-and-forth translation, recursive translation and bi-directional translation, is the process of translating a word, phrase or text into another language (forward translation), then translating the result back into the original language (back translation), using machine translation (MT) software.
It is often used by laypeople to evaluate a machine translation system, or to test whether a text is suitable for MT when they are unfamiliar with the target language. Because the resulting text can often differ substantially from the original, RTT can also be a source of entertainment*.

When we translate the paragraph below…

…with SYSTRAN Pure Neural™ Machine Translation (PNMT™) we get the translation into French : Continue reading

Pure Neural™ Machine Translation (PNMT™) Beta Test

by Lori Thicke Founder & CEO at Lexcelera

neural

Yesterday I translated our company presentation with Systran’s new Pure Neural™ Machine Translation (PNMT™) engine, and I was amazed at the results.

The presentation in question was a complete overview of all of our services, 59 pages of French text that was edited three separate times to make sure the quality was perfect. (Thanks Faten, Boris and Laurence!)

Then, two days ago, just as I was putting the finishing touches on the presentation for a response to an RFP (Request For Proposals), I found out that our prospective client (a major French manufacturer) wanted our response in English. I had just one day to deliver 59 pages of perfect English content!

Let me give you some background to explain why I, the CEO of a translation company, decided to use Neural Machine Translation for one of our most important commercial documents for one of our most important tenders.

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We are SYSTRAN and we love languages…

Click here to read the french version

SYSTRAN Banner

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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