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JP Translation System With Emotion Recognition?

JP Translation System With Emotion Recognition? | Language Tech Market News | Scoop.it

The Japanese Internal Affairs and Communications Ministry plans to develop by around 2020 a more precise automatic translation system utilizing artificial intelligence that reads facial expressions. The system will analyze a speaker’s facial expressions and scan the environment they are in to determine the context of the situation, resulting in translated dialogue that reflects feelings such as delight, anger, sorrow and pleasure. The ministry aims to use the system to support companies’ moves to expand overseas, as well as businesses catering to foreign tourists visiting Japan.
The ministry expects the system will be used for teleconferencing between Japan and other countries and for translating online videos.

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Gartner: NLU Will Help Emotion Perception in Personal Devices

Gartner: NLU Will Help Emotion Perception in Personal Devices | Language Tech Market News | Scoop.it

"Beyond smartphones and connected home devices, wearables and connected vehicles will collect, analyze and process users' emotional data via computer vision, audio or sensors capturing behavioral data to adapt or respond to a user's wants and needs.” 
The analyst firm also made some prediction about the development of personal devices, namely that the majority of device vendors (60%) will use third-party AI cloud services to enhance functionality and services by 2020.
A major catalyst on this front would be the increased usage of VPAs and natural-language technologies – which are technologies that marketers should well consider tapping into even if they are not device makers.

LT-Innovate's insight:

Language analysis as interface to emotional and personality states will become the new graphology.  

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AI-driven Emotional Intelligence Could Give Hospitals a Competitive Edge

AI-driven Emotional Intelligence Could Give Hospitals a Competitive Edge | Language Tech Market News | Scoop.it

 

A Tel Aviv-based startup called Beyond Verbal is working on analytics tools that could work with Alexa et al. to gain insight into behavioral and vocal patterns. In the not so far future, our aim is to add vocal biomarker analysis to our feature set enabling virtual private assistants to analyze your voice for specific health conditions," said the company's CEO Yuval Mor in June.

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How AI is Learning How to Tell Stories

How AI is Learning How to Tell Stories | Language Tech Market News | Scoop.it

Researchers at MIT Media Lab have just published a detailed blog with consulting firm McKinsey & Company about their results.
They had a deep neural network watch thousands of sections of films, TV and short online videos on Vimeo, and guess the emotionally special moments – the emotional arc.
"Think about this for a moment: machines can view an untagged video and create an emotional arc for the story based on all of its audio and visual elements," say the researchers.
"That’s something we’ve never seen before." People then watched the same clips, labeling which aspects had the strongest emotional power. The neural network then learned how to accurately predict audience engagement of a video on Twitter.

LT-Innovate's insight:

You could imagine an automated editor layer inserted into any textual/audio/video narrative system that compares the emotional quality of the story (its emotional arc) to some secret norm and evaluates the story accordingly for different emotional moments. 

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@Sogou Search Engine Working on Lip-reading and Divorce advice

@Sogou Search Engine Working on Lip-reading and Divorce advice | Language Tech Market News | Scoop.it

Lip reading is among the technologies Sogou unveiled at the Wuzhen World Internet Conference. When speakers are directly facing the camera, the system can “read” inaudible speech by analysing lip movements. The technology puts the firm on par with Google’s DeepMind artificial intelligence division.
Sogou is also upgrading its simultaneous interpretation system to add “emotion” to the translated voice output, Wang disclosed.
Sougou’s research on language processing is supported by the largest number of Chinese character inputs and include a daily average of more than 300 million voice entries created by its users, according to the Beijing-based company.

LT-Innovate's insight:

The power of a very large, relatively homogenous population of single-language speakers. Available Chinese-language data may be on a par if not greater than that for very multi-dialectal English.

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