On stage, a woman takes a seat at the piano. She

a) sits on a bench as her sister plays with the doll.

b) smiles with someone as the music plays.

c) is in the crowd, watching the dancers.

d) nervously sets her fingers on the keys.

For you, that would be an easy question. But for a computer, it was pretty hard. While humans answered more than 88 percent of the test questions correctly, the lab’s A.I. systems hovered around 60 percent. Among experts — those who know just how difficult it is to build systems that understand natural language — that was an impressive number.

Read more.

intelligence research to keep track of trends in the fast-paced field. In their second AI Index Report, published December 12, the group reported that the field has increasingly focused attention on language processing – how AI learns and understands human languages – and has expanded its global reach. The group also took the first snapshot of diversity in AI with an eye to tracking those metrics over time.

This information helps investors and governmental agencies determine how to allocate resources and provides updates for people whose lives will be affected by new developments in AI. The report was kickstarted by AI100, a collaboration of researchers who felt it was important to be tracking the progress of the field. It is  now overseen by Yoav Shoham, professor of computer science, emeritus, under Stanford’s Human-Centered AI Initiative.

Read more here.

limited within geographical boundaries or borders of only one large enterprise. As an increasing number of smaller companies enter the foreign market to assert their presence worldwide, the need to overcome language barriers is as a result higher than ever.

Read more. 

agencies typically involves a lot of manual work. Each language involved with every translation project generates overhead and requires email/phone interactions, increasing the cost and turnaround time of the project.

Overhead varies between companies as some agencies use more or less advanced translation management systems (TMS). Regardless, traditional agencies can typically handle up to several thousand projects a month at most—even those who leverage technology are essentially “manual” agencies in their DNA.

Read  more. 

master’s degree. The MA in Global Communication and Applied Translation (MA in GCAT) is a joint venture between Carnegie Mellon University’s (CMU’s) Department of English and Department of Modern Languages.

CMU is well-known for its language technologies department, which is home to the NeuLab, a dedicated natural language processing and machine learning research lab, headed up by Assistant Professor and leading light in machine translation research Graham Neubig.

Read more. 

translate English into Chinese and German in real time, in move to challenge a rival product from Google.

So far, many translation services online allow users to say or write a sentence, but there is a lag before it proceeds to serve up a translation. In contrast, Baidu's so-called simultaneous translation tool allows sentences to be translated almost instantly — much like a digital version of what interpreters do.

The product is a breakthrough for Baidu which has been investing heavily in AI for the past few years, hoping to build the future of its business on the technology.

Read more here. 

technologies ranging from natural language processing to machine translation is enjoying a resurgence thanks to AI.

Basically every language-related, AI-powered technology is driving demand, from speech recognition, sentiment analysis, question-answering and summarization, and of course, neural machine translation (NMT). Language data had always been necessary for technologies such as statistical MT, but NMT and any neural network-based solution is even more data hungry. What’s more, these technologies require high quality, domain-specific language data to provide equally high quality output.

Read more. 

on the fly. Siri Ventures, a corporate venture capital company backed by Sansiri, one of the biggest real estate developers in Thailand, has joined the growing number of companies betting big on smart home applications.

Sarunya Aroonsirichoke, Product Manager at Siri Ventures, told Slator in an email interview that the reason for this is that the company has gone beyond selling just properties.

Read more. 

Google Senior Webmaster Trends Analyst John Muellersaid Google could possibly be fooled by machine translated content when it comes to ranking search results.

According to SERoundtable, Mueller was asked in one of their regular Google Webmasters Hangouts sessions whether Google will now rank automatically translated content as recent developments in neural machine translation (NMT) have made machine translated content much more fluent.

Read more. 

companies in the past few years.

Advances in language technology have indeed been enabling various parts of the translation workflow to do just that. Translation memory and computer-assisted translation, for instance, offer linguists a productivity boost. Meanwhile, translation management systems give project managers and various stakeholders in the localization pipeline the ability to seamlessly handle complex project requirements.

Read more. 

verbalizes internally but does not actually speak aloud.

The system consists of a wearable device and an associated computing system. Electrodes in the device pick up neuromuscular signals in the jaw and face that are triggered by internal verbalizations -- saying words "in your head" -- but are undetectable to the human eye. The signals are fed to a machine-learning system that has been trained to correlate particular signals with particular words.

The device also includes a pair of bone-conduction headphones, which transmit vibrations through the bones of the face to the inner ear. Because they don't obstruct the ear canal, the headphones enable the system to convey information to the user without interrupting conversation or otherwise interfering with the user's auditory experience.

Read more. 

When a business expands into a foreign market, one of its top priorities is providing accurate and culturally specific translations of any company or product-related information, marketing materials and customer support data. This process of localization has become much more challenging due to the vast amount of communication facilitated by the Internet. Today, localization is a $35 billion annual industry.

have unlimited data or international plans, and are looking for ways to translate languages on the go.

Google recently announced that it’s going to begin offering its neural machine translation (NMT), AI-powered translation that can decipher and translate entire sentences into more natural sounding translations, offline.

While users could previously tap into offline translations through Google Translate, the translations were phrase based and didn't utilize the AI-capability of NMT, making the translations rougher.

Read more.

You probably use Google Translate online service or mobile application every now and then. You also must have noticed the recent online ads that promise to let you learn and speak a new language in a few weeks. How good, how true is all that?

The global, connected world is making it more important than ever to understand, to speak several languages and also to be able to translate between them automatically, instantly. It is all about communication, and the importance of the subject cannot be overstated. Whereas some good digital tools are available to address the need, the result often is mediocre; average in the best case.

Read More

MT technologies, NMT provides higher quality translation and is improving fast. Very fast. At its current rate of development, NMT is set to drastically change the traditional, human-based translation industry in as little as one to three years, impacting over 600,000 linguists and 21,000 language service providers (LSPs).

For customers, the age of NMT will lead to massive reductions in pricing and improvements in speed (even where humans are required).

To take full advantage of the NMT wave, however, LSPs and businesses need the capability to automatically handle a complex process involving simultaneous projects, high workloads, quality control, etc.

Read here

Nasdaq, neural machine translation (NMT) output by three of these four is hitting record highs.

Although NMT research output underwent a bit of downtime during December 2017 and the first couple of months of 2018, it seems to be in a resurgence since February 2018.

Read here

Facebook Messenger is adding automated translations to let buyers and sellers communicate when making purchases, the company said today. When users conduct a transaction through Facebook Marketplace and they receive a message in a language other than their default language, Messenger’s M bot will offer to translate it on their behalf. To start, translation features will be available in the United States for translating English to Spanish and vice versa.

Read More

Chances are you mostly need a translator app on your phone while you are traveling. But that’s also when you are most likely to not have any connectivity. While most translation apps still work when they are offline, they can’t use the sophisticated — and computationally intense — machine learning algorithms in the cloud that typically power them. Until now, that was also the case for the Microsoft Translator app on Amazon Fire, Android and iOS, but starting today, the app will actually run a slightly modified neural translation when offline (though iOS users may still have to wait a few days, as the update still has to be approved by Apple).

What’s interesting about this is that Microsoft  is able to do this on virtually any modern phone and that there is no need for a custom AI chip in them.

Read More

What would you do if you could understand any language?

From the universal translator of Star Trek to the Babel Fish from The Hitchhiker’s Guide to the Galaxy, sci-fi heads have always been captivated by the idea of rapid, seamless interpretation. But new tech has consumers seeing (and hearing) the future today, and it’s left content marketers with a number of important questions to consider.

A startup spun out of the National Taiwan University of Science and Technology is working on gloves that can translate sign-language gestures into text. Such a concept isn't new, by any means, but the elegance of Yingmi Tech's hardware deserves some special attention.

The company was actually founded by a team looking to build a less-kludgy way to control objects inside virtual reality. But it transpired that the same hardware was sophisticated enough to identify the motion of the hands as well as bends in the fingers.

Read the full article.

You know language technologies, and, in particular, machine translation, are in the midst of a hype cycle when Big 4 consulting firm Deloitte makes it a central theme in an artificial intelligence (AI) whitepaper. The 28-page paper published by the Deloitte Center for Government Insights explores how the US government can leverage AI to save on cost.

Deloitte says “AI programs can play games, recognize faces and speech, learn, and make informed decisions” and are improving “at an exponential rate”, which has resulted in everything from “self-driving cars to swarms of autonomous drones, from intelligent robots to stunningly accurate speech translation.” All that awesome tech could save the US government up to USD 41.1bn, the report estimates.

Read the full article.

Travel agents, pharmacy assistants and translators are already being replaced by robots, according to a report.

After a string of warnings that millions of workers will be replaced by machines, a study suggests this is happening now on a grand scale.

It claims that two thirds of the fastest declining jobs in Britain are being hit because of increased automation and advances in technology.

Read the full article.

Six engineering undergraduate students at the Massachusetts Institute of Technology (MIT) have designed a portable device that converts text to braille in real time. Their first prototype was created in a 15-hour hackathon in early 2016. Since that time, the device, called Tactile, has undergone extensive development. Now, it’s the size of a candy bar and completely portable. The students have applied for a patent for the device, although they are already working on its next iteration.

What really sets Tactile apart from other braille translators, though, is its low cost. Most of these devices are expensive and limited to the translation of text that is available digitally. For example, the HumanWare Braillant attaches to a computer or mobile device to translate text into braille, and it costs $2,595. Tactile’s creators hope to sell their device for less than $200.

Read the full article.

Facebook is claiming that a new approach to machine translation using convolutional neural networks (CNNs) can help translate languages more accurately (read: increase quality on a BLEU scale) and up to nine times faster than the traditional recurrent neural networks (RNNs). CEO Mark Zuckerberg himself announced the news in his own Facebook page.

The company’s bold claims were anchored on results of a study conducted by five members of Facebook’s Artificial Intelligence Research (FAIR) team and outlined in detail in a paper entitled “Convolutional Sequence to Sequence Learning.”

Read the full article.

Research study gives a complete list of all the leading players working in the global Language Translation Software market. Moreover, the financial status, company profiles, business strategies and policies, and the latest expansions in the global Language Translation Software market have been mentioned in the research study.

Read the full article.