When Neural Machine Translation is boosting Customer Service

In today’s accelerated globalization, booming e-commerce and customer service digitalization, the languages spoken by potential consumers come in hundreds. Global companies are faced with a problematic equation: while they might have centralized their customer service operations, it is still costly to recruit an agent for every language covered. It is nevertheless crucial to respond to customers in their native language quickly, efficiently and at minimal cost to achieve excellent Customer Service.

Breaking the language barrier

It’s simple: translating client emails instantly, responding to them in their language just as quickly or automatically displaying the most common answers in FAQ databases in multiple languages is a real Game Changer. For global Customer Service teams, the response time in foreign languages can be divided by 10 after Neural Machine Translation implementation! Calls are reduced with increased usage of a multilingual online knowledge base and customer satisfaction is higher than ever!

Data leakage is the biggest threat

More importantly, unsecured online translation tools, often used by customer service teams to understand customer queries in foreign languages expose companies to data leaks. The nature of interactions  during customer service operations can be as critical as sharing account information, credit card numbers, passwords and so on…

To guarantee complete security of your customer data, it’s absolutely key to rely on a provider that is able to provide the translation service on-premise or accessible via a private cloud. It is also true for internal support interactions. SYSTRAN also provide translation solutions for enterprise IT departments following a trend of global support services centralization, and allow them to manage technical support requests worldwide while ensuring user data security.

For more information on SYSTRAN’s multilingual solutions for customer service visit http://www.systransoft.com/business-solutions/customer-service-success/

Seven Tips for Better Translation Results

Whether you are using SYSTRAN’s Desktop, Enterprise Server, SaaS or online software, one question our IT Support is asked all the time is “How Can I Improve My Translation Output?” If incorrect or incomplete text or data is input into Machine Translation software, (also known as “garbage in, garbage out”) the outcome will, more often than not, also be incorrect or incomplete.

Here are seven tips to a better result:

  1. Use complete, grammatical sentences – Sentences should always start with a capital letter and end in either a period, exclamation point or question mark. A complete sentence always contains a verb, expresses an idea and makes sense standing alone.
  1. Avoid the passive voice – The passive voice is used to show interest in the person or object that experiences an action rather than the person or object that performs the action.
  1. Punctuation is important; clauses will translate best if separated by commas – Punctuation is the feature of writing that gives meaning to the written word. An error in punctuation can convey a completely different meaning to the one that is intended.
  1. Try to use simple, declarative sentences – A declarative sentence makes a statement, is in a present tense, and ends in a period. These are the most common sentences in the English language. It can either be a simple or compound sentence.
  1. Avoid ambiguity – To avoid ambiguity keep your sentences short, start with the subject, then the verb and end with the object. Use words and tenses consistently throughout.
  1. Avoid abbreviations, acronyms, jargon and colloquialisms – An abbreviation or acronym should first be spelled out if there are to be used consistently in a document. Colloquialisms are informal forms of speech and should be used mainly for speaking and not writing. Abbreviations, acronyms and jargon can be added to your User Dictionary or Translation Memories.
  1. Use your Dictionary Manager – SYSTRAN software includes a feature called the Dictionary Manager, which allows you to create your own dictionaries to supplement or override the main dictionary that comes with the program.  Using this feature can make substantial improvements to the translation.

The accuracy of the translation varies with the input.  If the input text is grammatically correct and unambiguous, it should translate well enough to convey the gist of what’s been written.

By: Ashley Shuler, Technical Support Analyst and Brooke Palm, Director of Customer Care SYSTRAN Software, Inc.

This was SYSTRAN Community Day’18!

Last week we hosted the 2018 edition of SYSTRAN Community Day! The conference was an exciting day full of energy, from Jean Senellart’s opening speech to our client success stories and celebrating SYSTRAN 50th anniversary! Here is a quick look at the conference highlights:

Jean Senellart announces SYSTRAN marketplace, a platform connecting the expertise of neural model trainers with the needs of industrial MT users

Jean Senellart, CEO of SYSTRAN France and CTO of the group opened the conference with a bold statement: the high quality of Neural Machine Translation has “commoditized” Machine Translation. As a commodity, NMT framework provides raw technology that needs to be refined, adapted and integrated for any industrial usage. After a look at the available NMT open source frameworks, including OpenNMT, cofounded and actively maintained by SYSTRAN, he made clear that streamlined training processes and data quality are the most crucial points to industrialize high quality neural machine translation.

Jean concluded his talk with the announcement of SYSTRAN marketplace, an open online platform where language experts have access to best of breed technology and framework to build, share, and sell language or domain models that can be accessed by industrial users. They will be able to select among hundreds of available models for any language pair and share feedback or evolution requests as per their specific needs.

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SYSTRAN presents its latest translation engines: huge quality & speed improvement!

The latest version of our AI-powered Translation Software designed for Businesses

SYSTRAN Pure Neural® Server is our new generation of enterprise translation software based on Artificial Intelligence and Neural networks. It provides outstanding professional quality with the highest standards in data safety.

Our R&D team, extremely active to provide corporate users with state-of-the-art translation technology tailored for business, just released a new generation of Neural MT engines. SYSTRAN new engines are developed with OpenNMT-tf, our AI framework using latest TensorFlow features, and backed by a proprietary new training process: Infinite Training.

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Open Source, Multilingual AI and Artificial Neural Networks : The new Holy Grail for the GAFA

Since 2016, there has been a sharp increase in open source machine translation projects based on neural networks or Neural Machine Translation (NMT) led by companies such as Google, Facebook and SYSTRAN. Why have machine translation and NMT-related innovations become the new Holy Grail for tech companies? And does the future of these companies rely on machine translation?

Never before has a technological field undergone so much disruption in such a short time. Invented in the 1960s, machine translation was first based on grammatical and syntactical rules until 2007. Statistical modelling (known as statistical translation or SMT), which matured particularly due to the abundance of data, then took over. Although statistical translation was introduced by IBM in the 1990s, it took 15 years for the technology to reach mass adoption. Neural Machine Translation on the other hand, only took two years to be widely adopted by the industry after being introduced by academia in 2014, showing the acceleration of innovation in this field. Machine translation is currently experiencing a golden age of technology.

From Big Data to Good Data

Not only have these successive waves of technology differed in their pace of development and adoption, but their key strengths or “core values” have also changed. In rule-based translation, value was brought by code and accumulated linguistic resources. For statistical models, the amount of data was paramount. The more data you had, the better the quality of your translation and your evaluation via the BLEU score (Bilingual Evaluation Understudy, the most widely used algorithm measuring machine translation quality). Now, the move to Machine translation based on neural networks and Deep Learning is well underway and has brought about major changes. The engines are trained to learn language as a child does, progressing step by step. The challenge is not only to process exponential data (Big Data) but more importantly to feed the engines the most qualitative data possible. Hence the interest in “Good data.”

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SYSTRAN Celebrates 50 Years in Business

SYSTRAN

SYSTRAN celebrates its golden anniversary as a machine translation company by looking back at their most memorable milestones.

In the last 50 years, SYSTRAN has had the great pleasure of delivering machine translation capabilities to the Fortune 500, unicorn start-ups, education institutions, non-profits, government communities and LSPs worldwide. They’ve arrived at a unique vantage point across industries such as banking, finance, manufacturing, legal, internet, security, software, wearable devices and IoT.

“To have experienced decades of SYSTRAN’s impact on technology and culture has been a gift,” says Denis A. Gachot, CEO of SYSTRAN Software Inc. “However, what I find more inspiring is the intention of our founder Peter Toma when starting SYSTRAN.”

“I felt deeply that I had to devote my energy to the elimination of world conflict causing factors. As a first step to overcome the language problem, I felt that I should know as many languages as possible and use technology so others could be understood.” – Peter Toma

From powering the translation that helped the U.S. and Soviet astronauts communicate, bringing on-line translation to the internet and assisting the F500 corporations to collaborate globally, these moments not only commemorate their longevity, but they also show their values.

Commenting on reaching 50, Chairman Mr. Chang-Jin Ji believes that SYSTRAN would not be celebrating today if it was not for the dedication of employees around the globe to customer support and innovation. “I truly thank them and the loyal support we have received from our customers.”

Looking to the future, this month SYSTRAN will launch a new generation of their server solution, SYSTRAN Pure Neural® Server, that pushes the quality and fluency boundary further than ever before explains Jean Senellart, Global CTO of SYSTRAN. “This new release benefits from the state-of-the-art research in neural translation and brings to our customers these technologies for their specialized models in a fully integrated solution. Our commitment to Open Source through the OpenNMT project, now comprising more than 1,600 members, has been pushing our development teams to achieve excellence, and is raising the bar for the whole industry.”

See SYSTRAN’s most memorable moments in this commemorative video.

Contact: | Craig Stern | Director of Marketing | craig.stern@systrangroup.com

Complying with MiFID II: 4 reasons why you need an intelligent translation solution

As of January 3rd 2018, companies in the financial industry operating in Europe are required by law to fully comply with the new MiFID II regulation. A good portion of the new rules requires translating various documents for a multilingual audience.

With that in mind, here are four reasons why you need neural machine translation to help you lead your compliance project to success:

1 – Effortlessly translate detailed information on tons of transactions

2 – Easily provide investors with multilingual research reports and articles

3 – Produce E-Learning and other company material to educate employees across the EU on complying with these new regulations

4 – Translate contracts and other official investment documents 

You can find the whole infographic here.

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Innovation & Security for Critical Manufacturing: MANUSEC Summit in Munich, we’ll be there!

To start off 2018 right, we are participating in our first event of the year: The MANUSEC 2018 as an official sponsor.

The two-day event will take place on February 7th8th 2018 in Munich and will mainly focus on the innovations and advancements being made in Cyber Security for the manufacturing industry.

We therefore invite you to join us and attend our speaker session on February 7th at 11:50 AM UTC+1: “Keep your translated data safe by using a secure and tailored solution based on the latest AI innovations”

Our account manager Loïc RENE, in charge of the manufacturing and automotive industry will be your main contact there. Please feel free to get in touch with him before or during the event to arrange a meeting onsite.

We cannot wait to meet you there! Benefit from 25% off with the code SYSTRAN25 at online registration.

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Artificial Intelligence: And You, How Will You Raise Your AI?

[This article originally appeared on Kirti Vashee’s Blog]

This is the final post for the 2017 year, a guest post by Jean Senellart who has been a serious MT practitioner for around 40 years, with deep expertise in all the technology paradigms that have been used to do machine translation. SYSTRAN has recently been running tests building MT systems with different datasets and parameters to evaluate how data and parameter variation affect MT output quality. As Jean said:

” We are continuously feeding data to a collection of models with different parameters – and at each iteration, we change the parameters. We have systems that are being evaluated in this setup for about 2 months and we see that they continue to learn.”

This is more of a vision statement about the future evolution of this (MT) technology, where they continue to learn and improve, rather than a direct reporting of experimental results, and I think is a fitting way to end the year in this blog.

It is very clear to most of us that deep learning based approaches are the way forward for continued MT technology evolution. However, skill with this technology will come with experimentation and understanding of data quality and control parameters. Babies learn by exploration and experimentation, and maybe we need to approach our continued learning, in the same way, learning from purposeful play. Is this not the way that intelligence evolves? Many experts say that AI is going to be driving learning and evolution in business practices in almost every sphere of business.

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Meet us at European Manufacturing Summit and discover how AI enhances multilingual collaboration & content production

Meet us at EUROPEAN MANUFACTURING SUMMIT 2017 – 27-29 th November – and discover how Artificial Intelligence enhances multilingual collaboration & content production. We will handle a speaking session the Day 2, 28th at 2:40PM: “Supporting Lean Manufacturing Efforts with Machine Translation Technology

EMS Summit 2017

Today’s Manufacturers are more than ever embracing the digital age and globalization. Global organizations must become more inter-connected to enhance their real-time multilingual collaboration.

To support global lean manufacturing efforts, it is essential to integrate machine translation into the core of the value chain. This will break down language barriers while reducing time to market and achieve the desired levels of quality and cost.

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