Secure Automated Translation: an essential tool for data governance in accordance with Basel & Solvency requirements

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Secure Automated Translation

Following the publication of the Basel (II and III) and Solvency Regulations, implementing Governance, Risk and Compliance (GRC) practices within financial institutions has gained predominance. To meet the challenges of data governance stated in the pillars of these regulations, companies have multiplied their efforts to recruit the best in GRC concerning Risk Management, Internal control, Internal Audit and Compliance.

According to a study conducted by the consulting company Optimind Winter and mandated by the Observatoire des métiers de la Banque (Banking Career Observatory)[1], “Banking companies are also victims of new risks and must create new job profiles to deal with these new challenges. GRC departments must face new challenges, such as coverage of systemic risk, development of Cloud Computing or Mobile Bank (technological nomadism).” Here, we refer to digitalizing the banking sector and using the Internet to manage personal bank accounts. Banks and insurance companies have thus implemented solutions to protect their customers’ data against cyber-attacks. While the efforts made to secure customer data have proven effective, the threat now lies within financial companies in their daily workflow.

Along with new working methods, a new phenomenon has emerged, known as “Shadow IT,” which is any application or method of transmitting information used in a business process without the endorsement of the internal IS department. Often unaware of its existence, IT departments don’t provide any support. Such processes generate "informal" and non-controlled data that can contravene existing standards and regulations such as Basel and Solvency. Continue reading

Translate within extended enterprises. What does that mean? – Part I

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AFNET, a non-profit society for boosting the digital transformation within vertical industries

AFNET is a French non-profit organization that promotes best practices for processes within the extended enterprises. This society introduces Internet in France in 1992 and was the owner for delivering Internet access to the very first users, mainly in universities.

Since this early age, AFNET has been continuing to promote good practices for enterprises within their ecosystem of suppliers, partners and key customers. These IT practices consist on standards, a common information system, and a partner framework for co-working in confidence.

Today, the best approach consists to leverage industry verticals to build open systems for digital transaction, content collaboration and product design.

Corporations are grouped within industry verticals and are highly dependent themselves. Just a few examples: Do you know that less than 20% of Dassault Rafale airplane parts are done by Dassault Aviation itself? Do you know that behind an Airbus air plane, there is a network of more than 1,200 different suppliers structured by more than 5 depth levels?

To be competitive and efficient within our globalized world, the European aerospace industry had organized itself with AFNET expert assistance to create a common information system named BoostAeroSpace: AirSupply as the platform for managing the supply chain, AirCollab as the platform for data communication exchange and Airdesign as the platform for product design. All these highly-secured platforms managed by the nonprofit organization and financed by all aerospace members make a strong asset that contributes to Airbus success.

Similar projects are in progress today for automotive, energy, travels, that leverage aerospace good practices. All of them share the common vision of the extended enterprise. Continue reading

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

Discover the first issue of Purely Neural Machine Translation insight

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 Demos Two New Integrations for Relativity at Ing3nious’ SoCal E-Discovery & Information Governance Retreat

This article was originally published on PR Newswire SYSTRAN Demos Two New Integrations for Relativity at Ing3nious’ SoCal E-Discovery & Information Governance Retreat

screen-shot-2016-11-16-at-1-54-07-pmSYSTRAN, a global leader in language translation technology, demonstrated two new integrations for SYSTRAN’s offering of Relativity at Ing3nious’ SoCal E-discovery & Information Governance Retreat, November 13-14.
SYSTRAN demonstrated two new integrations, aDiscovery and Anonymizer, for SYSTRAN’s offering of Relativity at the event. The aDiscovery feature will aid in audio discovery by transcribing audio files, detecting the source language and then translating the content. Anonymizer applies rigorous anonymization techniques to the full text and metadata of electronic documents within Relativity.

20161114_171147Anonymization can be used to mask identifying details in documents such as names, addresses, identification numbers, places, amounts and so forth when reading the anonymized documents; however, anonymized documents retain sufficient information for most relevancy reviews. Users also have the ability to “pseudononymize” selected names replacing pre-identified names with chosen pseudonyms on a mass basis to provide another option for privacy protection.

By 2020, Gartner predicts that 80 percent of litigation will involve multiple languages. The features are meant to assist with multi-language or cross-border e-discovery, giving legal teams a cost-effective method to translate files efficiently.

“These new integrations are going to change the way modern day legal teams handle multi-language files during e-discovery by maximizing productivity through automatic translation and Natural Language Processing (NLP),” says Ken Behan, SYSTRAN Vice President of Sales & Marketing. “These methods are far more efficient than manual translation and will save firms time and money during the e-discovery process.”

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In addition to the new integrations, SYSTRAN’s offering for Relativity automatically detects languages of files, translates documents that have multiple languages, and bulk translates using the Mass Action feature in Relativity. Organizations using Relativity are also able to support their billing process by accurately reflecting the workload completed.

To learn more about SYSTRAN’s offering of Relativity visit http://www.systransoft.com/translation-products/integrations/cmless-for-relativity.

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

Related Links

SYSTRAN for Relativity – More Information

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This article was originally published on PR Newswire  SYSTRAN Demos Two New Integrations for Relativity at Ing3nious’ SoCal E-Discovery & Information Governance Retreat

Voyage en traduction automatique

« Mais enfin, papa, tu ne vas pas aller là ! La traduction automatique, ça marche pas ! c’est pourri …», ainsi s’exprime la fille de l’auteur, 19 ans. Trait générationnel, elle est spontanée, directe.
L’auteur se gratte le front, légèrement ébranlé. Dans la main, il tient sa proposition d’embauche chez le leader mondial de la « machine translation ».

« Mais pourquoi dis-tu ça ? » Continue reading

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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How does Neural Machine Translation work?

The representation of meaning in Neural, Rule-Based and Phrase-Based Machine Translation

In this issue of step-by-step articles, we explain how neural machine translation (NMT) works and compare it with existing technologies: rule-based engines (RBMT) and phrase-based engines (PBMT, the most popular being Statistical Machine Translation – SMT).

The results obtained from Neural Machine Translation are amazing, in particular, the neural network’s paraphrasing. It almost seems as if the neural network really “understands” the sentence to translate. In this first article, we are interested in “meaning,” that which gives an idea of the type of semantic knowledge the neural networks use to translate.

Let us start with a glimpse of how the 3 technologies work, the different steps of each translation process and the resources that each technology uses to translate. Then we will take a look at a few examples and compare what each technology must do to translate them correctly.

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