#科技头条#【打打字,就能知道你的心情】

#科技头条#【打打字,就能知道你的心情】你知道电脑通过你打字的方式(平率、力度、按键方式等)就能猜出你的心情吗?近期,伊斯兰理工大学的研究者们让25名被试输入一段样文,并让电脑通过打字方式分析被试的情绪,结果70%的电脑分辨结果符合真实情况。其中,电脑分辨正确率最高的是高兴(87%)和愤怒(81%)。研究者表明这一研究结果将有助于发展更为高效、亲切的人机互动。

http://www.dailymail.co.uk/sciencetech/article-2793797/you-type-computer-guesses-mood-based-typing-style-lead-smarter-ai.html

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You are what you TYPE: Computer guesses your mood based on your typing style - and it could lead to smarter AI

  • Islamic University of Technology in Bangladesh researchers studied typing
  • They found that the way a person types can reveal how they are feeling
  • In the study 25 people were asked to write a section of a book
  • A computer programme then analysed their typing style at the time
  • It was able to predict 70 per cent of the time how they were feeling
  • Joy was predicted successfully most often and least successful was sadness
  • The researchers say this could lead to smarter artificial intelligence in future 

A computer programme has been used to predict how people are feeling when they type.

In a study participants were asked to type a particular phrase and the programme then estimated if they were happy, sad and so on.

Remarkably it was correct 70 per cent of the time, and the findings could lead to smarter artificial intelligence in the future.

The study published in the journal Behaviour and Information Technology was carried out by researchers at the Islamic University of Technology in Bangladesh, reports Live Science.

In the research 25 people ranging from 15 to 40 years old were asked to retype two paragraphs from Alice"s Adventures in Wonderland by Lewis Carroll.

 

hey also had to enter their emotional state every 30 minutes while doing their regular activities on the computer.

WHAT DO WE TYPE MOST OFTEN?

This allowed the programme an opportunity to understand how their emotions changed their typing style.

Moods tested were joy, fear, anger, sadness, disgust, shame and guilt.

The result was that the programme could identify a person"s mood correctly 70 per cent of the time.

It was most successful in identifying joyfulness with an 87 per cent success rating, while sadness was the least accurate at 60 per cent.

The researchers noted that the participants were less likely to input data when they were in a bad mood, which may explain the inaccuracy of the latter result.

However the findings could have important implications for artificial intelligence, and it may allow computers to engage with us in a more friendly manner.

"If we could build any system that is intelligent enough to interact with humans that involves emotions - that is, it can detect user emotions and change its behavior accordingly - then using machines could be more effective and friendly," the researchers wrote.

For example, this could enable pop-up ads to be tailored to how you are feeling at the moment.

Or, when looking for a movie on Netflix, perhaps an algorithm could make suggestions for films that would match your mood.

 

 

 

 


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