Language Learning


Predictions for Artificial Intelligence in 2018 Language learning: Ask AI r...

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Predictions for Artificial Intelligence in 2018 Language learning: Ask AI researchers what their next big target is, and they are likely to mention language. The hope is that techniques that have produced spectacular progress in voice and image recognition, among other areas, may also help computers parse and generate language more effectively. This is a long-standing goal in artificial intelligence, and the prospect of computers communicating and interacting with us using language is a fascinating one. Better language understanding would make machines a whole lot more useful. But the challenge is a formidable one, given the complexity, subtlety, and power of language.


A Review of Statistical Language Learning

AI Magazine

Several factors have led to the increase in interest in this field, which is heavily influenced by techniques from speech processing. One major factor is the recent availability of large online text collections. Another is a disillusionment with traditional AIbased approaches to parsing and natural language processing (NLP). Charniak is recognized as a distinguished contributor to what he calls traditional AI NLP, which is why it is all the more significant that in the Preface, when speaking of his recent transition to the statistical approach, he writes … few, if any, consider the traditional study of language from an artificial-intelligence point of view a "hot" area of research. A great deal of work is still done on specific NLP problems, from grammatical issues to stylistic considerations, but for me at least it is increasingly hard to believe that it will shed light on broader problems, since it has steadfastly refused to do so in the past.


Interactive Language Learning - The Stanford Natural Language Processing Group

@machinelearnbot

Today, natural language interfaces (NLIs) on computers or phones are often trained once and deployed, and users must just live with their limitations. Allowing users to demonstrate or teach the computer appears to be a central component to enable more natural and usable NLIs. Examining language acquisition research, there is considerable evidence suggesting that human children require interactions to learn language, as opposed to passively absorbing language, such as when watching TV (Kuhl et al., 2003, Sachs et al., 1981). Research suggests that when learning a language, rather than consciously analyzing increasingly complex linguistic structures (e.g. In contrast, the standard machine learning dataset setting has no interaction.


Microsoft taps AI for language learning app - Mobile World Live

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Microsoft took the wraps off a language learning app it described as "an always available, artificially intelligent" assistant. The app, Microsoft Learn Chinese, uses speech and natural language processing technology to enable learners to practice speaking the language. It uses "a suite of AI tools such as deep neural networks that have been tuned…to recognise what the language learners are trying to say and evaluate the speakers' pronunciation". Users get feedback in the form of scores, along with highlighted words which need improvement and links to sample audio to hear proper pronunciation. The machine-learning and neural networks powering the service are language-independent, Microsoft said.


AI-powered language learning promises to fast-track fluency

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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

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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.