Language Learning


AI-powered language learning promises to fast-track fluency

#artificialintelligence

A linguistics company is using AI to shorten the time it takes to learn a new language. It takes about 200 hours, using traditional methods, to gain basic proficiency in a new language. This AI-powered platform claims it can teach from beginner to fluency in just a few months – through once-daily 20 minute lessons. Learning a new language is hard. Some people seem to pick up new dialects with ease, but for the rest of us it's a trudge through rote memorization.


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#artificialintelligence

A linguistics company is using AI to shorten the time it takes to learn a new language. It takes about 200 hours, using traditional methods, to gain basic proficiency in a new language. This AI-powered platform claims it can teach from beginner to fluency in just a few months – through once-daily 20 minute lessons. Learning a new language is hard. Some people seem to pick up new dialects with ease, but for the rest of us it's a trudge through rote memorization.


Arduino powered and 3D printed, this robot translates to sign language

ZDNet

Sign language translators are scarce. Three engineering students from the University of Antwerp have novel solution: Cheap 3D printed humanoids that can translate to sign language on the fly. It's a solution that's only become possible with the converge of 3D printing, the massive popularity of microcontrollers like the Arduino Due, and falling prices for robotics components. ASLAN is an abbreviation which stands for: "Antwerp's Sign Language Actuating Node."


This 3D-printed robotic arm is built for sign language

#artificialintelligence

Or -- and this one is real -- a robot arm that can perform rudimentary sign language. Their solution is "Antwerp's Sign Language Actuating Node," or ASLAN. It's a robotic hand and forearm that can perform sign language letters and numbers. It also could be used to help teach sign language -- a robot doesn't get tired of repeating a gesture for you to learn.


Machines Are Developing Language Skills Inside Virtual Worlds

MIT Technology Review

Both the DeepMind and CMU approaches use deep reinforcement learning, popularized by DeepMind's Atari-playing AI. A neural network is fed raw pixel data from a virtual environment and uses rewards, like points in a computer game, to learn by trial and error (see "10 Breakthrough Technologies 2017: Reinforcement Learning"). By running through millions of training scenarios at accelerated speeds, both AI programs learned to associate words with particular objects and characteristics, which let them follow the commands. The millions of training runs required means Domingos is not convinced pure deep reinforcement learning will ever crack the real world.


Sign language turned to text with new electric glove

Daily Mail

An electric glove which can convert sign language into text messages has been unveiled by scientists. The device consists of a sports glove which has been fitted with nine stretchable sensors positioned over the knuckles. When a user bends their fingers or thumb to sign a letter, the sensors stretch, which causes an electrical signal to be produced. When a user bends their fingers or thumb to sign a letter, the sensors stretch, which causes an electrical signal to be produced.


Glove turns sign language into text for real-time translation

New Scientist

A new glove developed at the University of California, San Diego, can convert the 26 letters of American Sign Language (ASL) into text on a smartphone or computer screen. "For thousands of people in the UK, sign language is their first language," says Jesal Vishnuram, the technology research manager at the charity Action on Hearing Loss. In the UK, someone who is deaf is entitled to a sign language translator at work or when visiting a hospital, but at a train station, for example, it can be incredibly difficult to communicate with people who don't sign. The flexible sensors mean that you hardly notice that you are wearing the glove, says Timothy O'Connor who is working on the technology at the University of California, San Diego.


[R] From DeepMind: Grounded Language Learning in a Simulated 3D World • r/MachineLearning

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Abstract: We are increasingly surrounded by artificially intelligent technology that takes decisions and executes actions on our behalf. This creates a pressing need for general means to communicate with, instruct and guide artificial agents, with human language the most compelling means for such communication. Here we present an agent that learns to interpret language in a simulated 3D environment where it is rewarded for the successful execution of written instructions. Trained via a combination of reinforcement and unsupervised learning, and beginning with minimal prior knowledge, the agent learns to relate linguistic symbols to emergent perceptual representations of its physical surroundings and to pertinent sequences of actions.


Number of foreign students at public schools who lack Japanese language skills hits record high

The Japan Times

By prefecture, Aichi tops the list with 7,277 non-Japanese children with poor Japanese skills, followed by Kanagawa at 3,947, Tokyo at 2,932, Shizuoka at 2,673 and Osaka at 2,275. The survey also found 9,612 children who hold Japanese citizenship but have poor Japanese skills, needing remedial language instruction. Such children often have no choice but to learn basic Japanese at language schools or in classes provided by nonprofit groups like the center before entering a public school, Hazeki said. "There are a lot of language schools in Japan for international students, but Japan does not have a well-established system to train people who can teach Japanese to those elementary and junior high school children," Hazeki said.


Automatic sign language translators turn signing into text

New Scientist

Machine translation systems that convert sign language into text and back again are helping people who are deaf or have difficulty hearing to communicate with those who cannot sign. A sign language user can approach a bank teller and sign to the KinTrans camera that they'd like assistance, for example. KinTrans's machine learning algorithm translates each sign as it is made and then a separate algorithm turns those signs into a sentence that makes grammatical sense. KinTrans founder Mohamed Elwazer says his system can already recognise thousands of signs in both American and Arabic sign language with 98 per cent accuracy.