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[备考日记] 【揽瓜阁2.0】Day8 2020.06.22【人文科学-情绪】

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楼主
发表于 2020-6-21 20:28:22 | 只看该作者 回帖奖励 |倒序浏览 |阅读模式
  揽瓜阁俱乐部第二期
  Day8 2020.06.22


【人文科学-情绪】
Do not rely on facial expressions for how people are feeling
(591字 精读 必做篇)

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

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 recognisable 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.

As Lisa Feldman Barrett, one of the authors of the study, published in Psychological Science in the Public Interest, told the AAAS meeting in Seattle, “We surprised ourselves”. Dr Feldman Barrett is a psychologist at Northeastern University in Boston, Massachusetts, and along with her colleagues she found that, on average, adults in urban cultures scowled when they were angry 30% of the time. Which meant that some 70% of the time they did not scowl when angry. Instead, they did something else with their faces. People also scowled when they were not angry. “They scowl when they’re concentrating, they scowl when someone tells them a bad joke, they scowl when they have gas, they scowl for lots of reasons,” says Dr Feldman Barrett.

A scowl, the researchers concluded, is certainly one expression of anger. But it is not the only way people express that emotion. The ambiguous nature of facial expressions was not restricted to anger, but seemed valid for all six of the emotional categories that they examined: anger, disgust, fear, happiness, sadness and surprise.

All this raises questions about the efforts of information-technology companies to develop artificial-intelligence algorithms which can recognise 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 extract 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 cues, such 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 cited 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 view zoomed out to show 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 submit a video cv, and then this is analysed by a machine-learning system. And depending on your facial expressions, they hire you or not, which I find really stunning and not only based on the wrong hypothesis, but a dangerous hypothesis.”

Source: The Economist


【人文科学-情绪】
Real Laughs Motivate More Guffaws
(437字 2分42秒 精听 必做篇)

先做精听再核对原文哦~


"I thought you were downstair boxing chocolates." "Oh, they kicked me out of there. I kept pinching them to see what kind they were."[CLIP: I Love Lucy with laugh track]

Laugh tracks in television shows like I Love Lucy have been encouraging us to chuckle since the 1950s. But they originated even before that with old radio shows.

“If you just put out a comedy program on the radio, people didn’t necessarily realize it was supposed to be funny. So they started recording them with a live audience because then people had all the cues that they would get if they were at the theaters, say—of an audience response. And, indeed, laughter can be highly contagious.”

Sophie Scott is a cognitive neuroscientist at University College London. She and her team wondered whether adding laughter to a joke could also make it seem funnier. So they scoured the Internet for the most groan-worthy jokes they could find and enlisted the help of a professional comedian to record them.

“So things like ‘What’s the best day for cooking? Friday. How does a dinosaur pay its bills? Using tyrannosaurus checks,’ that kind of thing.And then we got people to rate how funny they were without any laughter added.”

The researchers paired the jokes with both spontaneous, involuntary laughter and with laughter that had been produced on demand.

"What do you recieve when you ask a lemon for help? Lemon aid."[CLIP: Lemonade joke with laughter]

They played these recordings to adults, some neurotypical and some on the autism spectrum.

“The main thing that we found was that the people with autism and the neurotypical controls were both influenced by laughter in the same way. So everybody found that the more intense the laughter, the funnier that made the joke. So everybody’s rating the jokes as even funnier when they’re paired with spontaneous laughter.”

That is, honest, involuntary laughter cued people to perceive the jokes as funnier more than fake, forced laughter did. And that result was universal: “I think we were expecting there to be some differences for the people with autism, and we did not find them.”

But autistic participants did find the jokes funnier overall.

“And I think what we’re seeing here is that the people with autism are more generous in their assessment of the jokes, I suspect, although that’s just one interpretation.”

The study appears in the journal Current Biology.

In future laughter experiments, the researchers plan to scan participants’ brains to better understand the neural systems responsible for tickling our funny bones. When they do, they may discover that dogs can’t operate an MRI machine, but CAT scan.

Source: Scientific American


【笔记格式要求】

精读笔记格式要求:
1.总结文章中心大意
2.总结分论点或每段段落大意
3.摘抄印象深刻或者觉得优美的句子
4.总结文章中的生词
5.记录阅读时间、总结时间、总时间

精听笔记格式要求:
1.逐句听写整篇文章
2.对照原文修改听写稿,标记出错原因
3.总结文章中心大意
4.总结精听过程中的生词
5.记录听写时间、总结时间、总时间

这里也给大家两点学习小建议哦~
精读:如遇到读不懂的复杂句,建议找出句子主干,分析句子成分,也可以尝试翻译句子来帮助理解~
精听:建议每句不要反复纠结听,如果听 5 遍都没听出来,那就跳过,等完成后再回听总结原因,时间宝贵,不要过于执着哦~


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沙发
 楼主| 发表于 2020-6-21 20:28:32 | 只看该作者
揽瓜阁俱乐部,自「language」一词谐音而来,是一个为帮助大家提升英语语言能力而建立的学习小团队。在这里,我们将定时发布涵盖各类话题的外刊语料,供大家练习精听、精读。同时还设置了严格的打卡机制,督促大家克服懒惰坚持学习。

同时我们也招募volunteer协助维护团队,确保学习活动顺利开展~大家一起营造积极向上的学习氛围~

想要提升英语能力的小伙伴,快快添加微信(theTOEFL)报名加入吧,让妥妥带你观尽天下新鲜事,览遍四海热议瓜~


如果你想加入,可以直接在本帖下完成你的学习笔记!如果想进入学习群聊,请直接联系妥妥。
板凳
发表于 2020-6-21 21:37:59 | 只看该作者
揽瓜阁 Day 8
Dovis 2020 6 22
精读 Do not rely on facial expressions for how people are feeling
一 文章大意
两千年来,人们仍然坚信表情时人类情绪的窗口。研究学者经分析面部表情与内在情绪关联之后,认为表情与情绪的对应关系并不是唯一的,也并非是在所有文化中都一致的,还需考虑情绪当下的情景。这对部分公司声称AI算法可以识别面部表情并读取内心情绪的说法造成了冲击。
二 段落总结
  • 两千年以来,面部表情仍被普遍认为是一种衡量他人感受的普遍有效的方法。
  • 经研究分析面部表情与内在情绪关联的论文之后,得出结论:没有科学证据表明,同一种面部表情所传递出的对应情感在所有文化场景中都一致的。
  • 该研究的作者之一提到,不同文化不同场景中,面部表情和内在情绪并不总是相同的。生气并不一定会皱眉,皱眉也并不一定是生气。
  • 以上研究得出结论:皱着眉头是愤怒的一种表达。 但这不是人们表达这种情感的唯一方式,这个结论同样适合其他情感类别。
  • 这个结论引起了人们对IT公司努力开发能够可识别出面部表情并计算内在情绪状态的AI算法的质疑。
  • 面部表情只是人们用来交流的许多非语言提示之一。 但机器对情感的识别不能了解情绪发生时的情景,也无法获取面部表情下的“言下之意”。
  • 举例说明,光凭静态的表情识别而忽略场景,很容易得出错误的情绪结论的。
  • 大多数时候连人类本身都无法猜到对方的情绪状态,所以公司声称可以通过AI算法来实现情绪识别,并将其应用在一些工作场景(如简历筛选)中,是错误且危险的做法。
三 生词摘录
outstretch 拉(伸)长;扩张;展开;伸展; 超越…的范围
四 句子摘抄
All this raises questions about the efforts of information-technology companies to develop artificial-intelligence algorithms which can recognise facial expressions and work out a person’s underlying emotional state.
五 用时记录
通读 4min 总结27min 共计32min

地板
发表于 2020-6-22 11:32:13 | 只看该作者
Day8打卡


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5#
发表于 2020-6-22 12:04:38 | 只看该作者
Day8

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6#
发表于 2020-6-22 12:11:11 | 只看该作者
D8

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7#
发表于 2020-6-22 14:31:50 | 只看该作者
阅读笔记

中心大意:自古希腊时期,哲学家们就认为脸部表情是洞察人心理和情绪状态的窗口。但现代的若干研究报告都指出,我们还难以对很多面部表情做出准备的当事人情绪推测。而近年流行的计算机识别技术对情绪识别其实也无能为力。

段落意思

第一段:自古希腊哲学家开始,就认为脸部表情是自我情绪的表现窗口。

第二段:但数百篇科研文献表明,面部表情并不能被有效识别出来。

第三段:研究者对这些“反直觉”的研究成果表示惊讶,他们发现70%的人在生气时不并会皱眉,相反,在做其他事情的时候,不生气时也会皱眉,比如专心致志的时候。

第四段:研究人员发现,皱着眉肯定是一种愤怒的表达,但在有其他情绪时也可能会皱眉。面部表情通常是模棱两可,难以识别的。

第五段:这些研究都加大了大家对利用计算机技术来对面部表情进行情绪识别的有效性的怀疑。

第六段:面部表情仅仅是人们用来交流时的众多非语言提示之一。研究者举例一张脸色鲜红,张嘴尖叫的照片给大家。

第七段:仅仅看这个面部表情,大家会以为是他很愤怒,但当看到更完整的照片时,才会发现这是一位运动员在张开双臂庆祝。

第八段:考虑到人们大部分时间里其实难以猜测出彼此的情绪,研究者认为计算机技术还无法做到仅仅对局部的面部照片或短视频进行准确的分析。


句子摘抄:

Two millennia on, facial expressions are still commonly thought to be a universally valid way to gauge other people’s feelings, irrespective of age, sex and culture.

The ambiguous nature of facial expressions was not restricted to anger, but seemed valid for all six of the

For a start, facial expression is but one of a number of non-verbal cues, such as body posture, that people use to communicate with each other.

Based on this alone, most participants said the man was extremely angry.

emotional categories that they examined: anger, disgust, fear, happiness, sadness and surprise.

A scowl, the researchers concluded, is certainly one expression of anger.

生词摘抄:

irrespective a.不考虑的,不顾虑的
recognisable a.可辨认的 可认识的
ambiguous a.模糊不清的

阅读时间 8分钟 总结时间 32分钟 共计 40分钟

听力笔记


中心大意:电视喜剧和广播喜剧里都有笑声的配音,认知神经科学家对这些笑话中添加的笑声是否会让其听上去更有趣,展开了专门的研究。

生词摘录:

cognitive a.认知的
neuroscientist 神经科学家
autism n.孤独症






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8#
发表于 2020-6-22 15:21:28 | 只看该作者
day 8 打卡

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9#
发表于 2020-6-22 16:01:42 | 只看该作者
Day8 打卡

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10#
发表于 2020-6-22 17:54:10 | 只看该作者
Day8

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