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Aristotle thought the face was a window ...

    Aristotle thought the face was a window onto a person’s mind. Cicero agreed. Two thousand years passed, and facial expressions are still commonly thought to be a universally valid way to judge other people’s feelings, irrespective of age, sex and culture. A raised eyebrow suggests confusion. A smile indicates happiness.

Or do they? An analysis of hundreds of research papers that examined the relationship between facial expressions and underlying emotions has uncovered a surprising conclusion: there is no good scientific evidence to suggest that there are such things as recognizable facial expressions for basic emotions which are universal across cultures. Just because a person is not smiling, the researchers found, does not mean that person is unhappy.

This may raise questions about the efforts of information-technology companies to develop artificial-intelligence algorithms (算法) which can recognize facial expressions and work out a person’s underlying emotional state. Microsoft, for example, claims its “Emotion API” is able to detect what people are feeling by examining video footage of them. Another of the study’s authors, however, expressed scepticism. Aleix Martinez, a computer engineer at Ohio State University, said that companies attempting to obtain emotions from images of faces have failed to understand the importance of context.

For a start, facial expression is but one of a number of non-verbal wayssuch as body posture, that people use to communicate with each other. Machine recognition of emotion needs to take account of these as well. But context can reach further than that. Dr Martinez mentioned an experiment in which participants were shown a close-up picture of a man’s face, which was bright red with his mouth open in a scream. Based on this alone, most participants said the man was extremely angry. Then the whole picture was shown. It was a football player with his arms outstretched, celebrating a goal. His angry-looking face was, in fact, a show of pure joy.

Given that people cannot guess each other’s emotional states most of the time, Dr Martinez sees no reason computers would be able to. “There are companies right now claiming to be able to do that and apply this to places I find really scary and dangerous, for example, in hiring people,” he says. “Some companies require you to present a video resume, which is analyzed by a machine-learning system. And depending on your facial expressions, they hire you or not, which I find really shocking.”

1.We can learn from the second paragraph that __________.

A.facial expressions are universal across cultures

B.it is hard to recognize some facial expressions

C.emotions and facial expressions may not be related

D.common facial expressions convey similar meanings

2.In the passage, the word “scepticism” (paragraph 3) is closest in meaning to “__________”.

A.similar interest B.fierce anger C.strong support D.great doubt

3.The experiment mentioned by Dr Martinez may prove that ___________.

A.facial expression is an important way to communicate

B.machine recognition of emotion is not reliable at all

C.facial expression is not the only way to detect feelings

D.people may misread facial expressions for lack of context

4.What does this passage mainly tell us?

A.Facial expressions are among the most universal forms of body language.

B.Computers can detect people’s mind by analyzing their facial expressions.

C.Facial expressions may not be the reliable reflection of a person’s emotions.

D.Companies can depend on machine recognition of emotion to hire people.

 

1.C 2.D 3.D 4.C 【解析】 本文是一篇说明文。人脸识别功能已经广泛应用于生活方方面面,但科学家近日发现,面部表情并不能精确地反映出本人的真实心情。 1.推理判断题。根据原文的“Just because a person is not smiling, the researchers found, does not mean that person is unhappy.(科学家发现,因为一个人不笑并不意味着这个人不开心)”,可以判断脸部表情与心情之间并没有必然联系。故选C项。 2.词句猜测题。根据原文的“Another of the study’s authors, however, expressed scepticism.(然而,另一位研究作者表示了怀疑)”,根据句中转折词however(然而),可以判断该处表达的意思与上文“Emotion API is able to detect what people are feeling by examining video footage of them.(表情APT能够通过检测视频来判别人们心中所想)”是相反的,即人脸识别并不能反应出人们内心真实心情。故选D项。 3.推理判断题。定位到第四段落,根据“Machine recognition of emotion needs to take account of these as well.(机器表情识别也需要考量上述因素(情境))”,及根据原文“His angry-looking face was, in fact, a show of pure joy.(事实上,他看起来愤怒的表情实际上是快乐的表情)”,可判断出如果脱离了具体情境,我们就无法正确解读面部表情。故选D项。 4.主旨大意题。全文都在讨论面部识别与人们内心情感之间的关系是否是正相关,作者通过引述科学家的言论“depending on your facial expressions, they hire you or not, which I find really shocking(凭借人脸表情识别来决定是否录用求职者,依我看是非常震惊的)”来例证脸部识别表情这一功能的不可靠,因为面部表情并非真正地反映出我们的真情实感。故选C项。
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