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.

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

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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

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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The use of machine translation in eDiscovery

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This article originally appeared on Kirti Vashee’s Blog.

There are some kinds of translation applications where MT just makes sense, and it would be foolish to even attempt these kinds of projects without decent MT technology as a foundation. Usually, this is because these applications have some combination of the following factors:

  • Very large volume of source content that simply could NOT be translated without MT in any useful time frame
  • Rapid turnaround requirement (days, hours or minutes) for the content to have any value to the translation consumers
  • A user tolerance for lower quality translations at least in early stages of information review
  • To enable information and document triage when dealing with large document collections and help to identify highest priority content from a large mass of undifferentiated content. This process also helps to identify the most important and relevant documents to send to higher quality human translation.
  • Translation Cost prohibitions (usually related to volume)

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SYSTRAN at the Digital Forensics and Analysis Summit

Digital SummitOn October 16-17th, SYSTRAN and its partner Relativity will be participating in the Digital Forensics & Analysis Summit as sponsors and exhibitors. The Digital Forensics & Analysis Summit is a two-day forum that will gather international experts from around the world in Abu Dhabi to share best practices on how technology is used in their forensics department to extract evidence that is able to stand up in trial.

Since information governance, forensics and eDiscovery procedures face mounting pressure from the growth of Electronic stored Information, legal standards and rules governing digital investigation requirements have also contributed to the rise in litigation and associated legal costs.

Within this environment, documents written in languages other than English, including data collection, processing and reviewing can pose major challenges, especially when ensuring the mandatory confidentiality of those procedures, as these typically forbid online translation. Organizations need to search by keyword and find relevant documents and emails in the appropriate languages while controlling costs and maximizing productivity. Therefore time-intensive human translation is usually not an option and the need for viable machine translation solutions becomes all the more apparent.

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Huffington Post Interview with Ken Behan – Have Multilingual Customers? Here’s a Solution for You

This article was originally published on The Huffington Post  Have Multilingual Customers? Here’s a Solution for You (Interview With Ken Behan)

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“Languages are intriguing and challenging at the same time”

As kids we were always intrigued by the way Google Translator worked. While it translated those famous French quotes for us, there were limitations which even Google couldn’t surpass. Since then, language has been a barrier— hindering our global crusades. Be it a worldwide competition or business meetups across countries, a common language would have been the best idea which sadly is pretty hard thing to materialize.

Even readers at the Huffingtonpost must have had difficulties with other country specific domains, offering great pieces of work which couldn’t be accessed— owing the language barrier.

Here we interview Ken Behan, Vice President, SYSTRAN Software Inc. and understand what sort of challenges we face when it comes to a multilingual platform like the Internet. We will be asking him about the process involved with translations and analysis apart from the levels of accuracy. Lastly, he will be talking about the company and what purposes it can serve, towards the common good of this society.

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6 Powerful Tips For Effective & Efficient Multi-Language Customer Support

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This gallery contains 12 photos.

1. Increase your deflection rate by translating your self-service knowledge centers into multiple languages. 2. Improve satisfaction with the self-service experience by setting expectations up front. 3. Scale customer service into new regions by supporting additional languages. 4. Respond to … Continue reading

At ISS World South Africa, SYSTRAN will showcase its MT and NLP solutions for Intelligence

At ISS World South Africa 2016, held in Johannesburg, from 10 to 12 of July, SYSYRAN will showcase its machine translation and Natural Language Processing solutions dedicated to Intelligence Community.

FlyerISSWorldSouthAfricaISS World South Africa is the world’s largest gathering of Southern Africa Law Enforcement, Intelligence and Homeland Security Analysts as well as Telecom Operators responsible for Lawful Interception, Hi-Tech Electronic Investigations and Network Intelligence Gathering (see the official website).

SYSTRAN will attend as a key technological provider of National Security agencies, Military Intelligence services, Law Enforcement Agencies, and Criminal intelligence units. SYSTRAN offers secured and offline translation servers which can easily be integrated in your existing intelligence platforms. In short, SYSTRAN, as a Natural Language Processing expert, facilitates Big Data processing in more than 45 foreign languages and ensures information security.

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