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“
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.
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)
On 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.
“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.
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 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.
ISS 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.
This summer, the social media sphere will be buzzing again with fans and athletes posting about the 2016 Summer Olympics in Rio de Janeiro, Brazil. It will be the first Olympic games to take place in South America. You can also expect networks, publishers, and brands to get in on the social media experience by generating more content than ever before.
Looking back to the London games in 2012, just the social media interactions on Twitter alone were vast in terms of engagement:
– On Twitter, there were 960K mentions for Bolt, 830K for Phelps, and 490K for Tom Daley (British diver who took the bronze) during the games.
– The first day of Olympics, there were 3 million tweets in total.
The numbers go on and on, especially when you take into account all the views, likes, tweets by sports teams, athletes, and brands. There are plenty of useful stats out there from archives of the first ever “Social Games” as most tech blogs described it.