On July 2, 2020, translation productivity and management software provider Memsource announced that one of the world’s largest private equity firms, US-based Carlyle Group, had acquired a majority stake in the company. Carlyle Group is one of the world’s largest private equity firms with over USD 80bn in assets under management and currently 181 portfolio companies.
memoQ is pleased to announce the release of its latest version, memoQ 9.4.
With this release, users get some clever new features, as well as enhancements to existing features that are designed to streamline workflow.
Read more on Slator.
It was just three years ago that Timekettle introduced its WT2 Plus translator earbuds to an audience eager for a device to instantaneously facilitate multilingual conversations. Now the company that has inspired a following in 120 countries around the world has created the Timekettle M2 – a product that takes translation capabilities to the next level while incorporating a function that customers have been clamoring for: Music and Phone-call.
Machine learning has significantly boosted automatic translation in recent years. Systems such as 2016’s GNMT (Google’s Neural Machine Translation System) have improved translation performance in over 100 languages. However, even today’s most advanced translation systems still lag behind human performance in almost all respects. For languages with high usage rates, plentiful data resources make it easy to improve technical capabilities. Translation improvements for low-resource languages however have not nearly come as quickly.
The new Apple iPhone operating system, iOS 14, will come with a Translate app; so revealed the tech giant on June 22, 2020 at the Apple Worldwide Developers Conference (WWDC 2020). iOS 14 will feature several updates to Siri, such as enabling it to send audio messages, help with offline translations, and support for new language pairs. Basically, Siri will enable iPhone users to have “entire conversations [that are] natural and easy, and have the ability to stay private” via offline mode.
Continue reading on Slator.
SLATE is an automated translation platform built on SDL’s Language Cloud platform and combines SDL Machine Translation with SDL’s in-house professional translators. It is self-serve, subscription-based, easy to use, and quickly delivers translations in a highly secure environment. “It’s the perfect blend of technology innovation and human expertise,” Djaouani told Slator.
Microsoft shipped another weekly update for the Microsoft Edge Dev Channel today, bringing the usual round of general improvements and fixes. There are a few new features included as well, the most notable of which is more languages that are supported for translating web content. Microsoft doesn’t outline what the new languages are, however.
As the localization industry adapts to global challenges and changes in the wake of the COVID-19 pandemic, the development of exciting new technologies and the publication of important research findings continue unabated. Join us for a brief look into some of the most important recent developments.
A number of Google users who accessed the “Download Your Data” tool via Takeout between October 30, 2019 and April 7, 2020 were probably surprised to receive an email saying that their data had been inadvertently sent to another Google user.
“We are writing to let you know that we recently found a technical issue with our ‘Google Translator Toolkit,’ a product we shut down in 2019,” the email from Google began. As reported by Slator last fall, Google Translator Toolkit, or GTT, was discontinued from December 2019. A cloud-based translation productivity (aka CAT) tool, GTT was likely shelved during the periodic clean-up of products that have been in maintenance-only mode for some time.
The European language technology innovator Tilde launches a revolutionary Dynamic Learning technology for machine translation. Tilde MT Dynamic Learning picks up human corrections in real time, thus significantly boosting the quality of machine translation. This novel technology was made possible thanks to the break-through research of the award-winning Tilde research team.
Read the full press release here.
InterpretCloud announces the launch of its InterpretCloud video remote interpreting solution, the most reliable and high-quality cloud-based solution for on-site and online events and meetings. InterpretCloud helps companies and individuals to communicate with their local and global audiences during live events and online meetings, anywhere, anytime, and in any language.
Most of us have not heard of machine translation for sign language, but it’s an exciting technological development that helps people who are deaf or hard of hearing communicate with the hearing world, most of which does not know sign language. Machine translation systems for sign-language can do this by automatically converting signs into text or spoken dialogue, then back into sign language, without needing a human interpreter.
Machine translation for sign language has been around since the 1970s, but it has been difficult for developers to perfect the technology because sign language constructs differ greatly from those of spoken languages.
Here are a few machine translation inventions from the past and some more recent developments on the market.
Daily orders and judgments of the Supreme Court will soon be translated into nine vernacular languages with the help of artificial intelligence (AI) tools developed in-house to reduce human intervention in translating judicial documents.
Senior officials in the Supreme Court registry told ThePrint the AI tools are being tested to achieve at least 90 per cent accuracy in translation. A committee headed by Justice L.N. Rao is supervising the project.
To help localize subtitles from English to other languages, such as Russian, Spanish, or Portuguese, Netflix developed a proof-of-concept AI model that can automatically simplify and translate subtitles to multiple languages.
The work is presented in a paper, Simplify-then-Translate: Automatic Preprocessing for Black-Box Machine Translation, published this month on the pre-print platform arXiv. The work is a collaboration between Netflix and Virginia Tech.
Students of RIT (Pranav & Ramaswamy under the guidance of our faculty Mrs. Subha. S) have developed an app to overcome the barriers of language in technical education. Their app enables the school and college students to input technical terms in English and gets detailed translation in their mother tongues such as description, visualisation and reference books. Unlike most other online platforms this app will suggest local authors and give context to the students with a native touch.
Crowdin, a localization management solution for tech companies, has unveiled its new product – Crowdin for Enterprise. The new platform is currently available via Public Beta and offers a completely new localization experience for business owners, project managers, translation specialists, developers, and all the non-tech teams involved.
BoostLink™ offers Language Service Organizations, healthcare providers, patients, and remote interpreters a secure, easy-to-use video conference option with the communication and privacy features they need. Continue reading here.
This post is the first in a series of upcoming posts focusing on the issue of quality evaluation of multiple MT systems. MT system selection has become a more important issue in recent times as users and buyers realize that potentially multiple MT systems can be viable for their needs, but would like to develop better, more informed selection procedures.
One year ago, we called the VIT hype a solution without a problem. In times of COVID-19 it has now become the solution to the problem.
Hugging Face is taking its first step into machine translation this week with the release of more than 1,000 models. Researchers trained models using unsupervised learning and the Open Parallel Corpus (OPUS). OPUS is a project undertaken by the University of Helsinki and global partners to gather and open-source a wide variety of language data sets, particularly for low resource languages. Low resource languages are those with less training data than more commonly used languages like English.
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