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  • Our emotions influence every aspect of our lives,

    我們的情緒會影響 日常生活的各個層面,

  • from our health and how we learn, to how we do business and make decisions,

    從我們的健康到如何學習、 如何做事、做決定,

  • big ones and small.

    無論事情大小都受此影響。

  • Our emotions also influence how we connect with one another.

    我們的情緒也會影響 我們如何與他人交流。

  • We've evolved to live in a world like this,

    我們已經進化到生活在 一個像這樣的世界,

  • but instead, we're living more and more of our lives like this --

    然而我們的生活卻愈來愈像這樣──

  • this is the text message from my daughter last night --

    這是我女兒昨晚傳來的簡訊──

  • in a world that's devoid of emotion.

    一個缺乏情感的世界。

  • So I'm on a mission to change that.

    所以我帶著使命要改變這種狀況。

  • I want to bring emotions back into our digital experiences.

    我想將情感重新注入數位體驗中。

  • I started on this path 15 years ago.

    我在 15 年前走上這條路。

  • I was a computer scientist in Egypt,

    當時我在埃及是電腦科學家,

  • and I had just gotten accepted to a Ph.D. program at Cambridge University.

    而且我才拿到劍橋大學 博士班的入學許可。

  • So I did something quite unusual

    所以我做了一件 對身為年輕新婚的埃及回教婦女來說

  • for a young newlywed Muslim Egyptian wife:

    相當不尋常的事:

  • With the support of my husband, who had to stay in Egypt,

    在我先生的支持下, 他留在埃及,

  • I packed my bags and I moved to England.

    我整理行囊搬到英格蘭。

  • At Cambridge, thousands of miles away from home,

    在劍橋,離家千里遠的地方,

  • I realized I was spending more hours with my laptop

    我發現我與筆電相處的時間,

  • than I did with any other human.

    遠超過與人交流的時間。

  • Yet despite this intimacy, my laptop had absolutely no idea how I was feeling.

    儘管與筆電相處如此親密, 它卻完全不了解我的感受,

  • It had no idea if I was happy,

    它不知道我是否開心,

  • having a bad day, or stressed, confused,

    今天順不順,是否緊張或困惑,

  • and so that got frustrating.

    所以那令我沮喪。

  • Even worse, as I communicated online with my family back home,

    更糟的是,在我上線 與遠方的家人聯絡時,

  • I felt that all my emotions disappeared in cyberspace.

    我覺得我的情感 在這虛擬空間裡消失無蹤。

  • I was homesick, I was lonely, and on some days I was actually crying,

    我好想家,我好孤單, 有些日子我真的哭了,

  • but all I had to communicate these emotions was this.

    但我所能傳達的只有這個。

  • (Laughter)

    (笑聲)

  • Today's technology has lots of I.Q., but no E.Q.;

    今天的科技有很多智商, 卻沒有情緒智商;

  • lots of cognitive intelligence, but no emotional intelligence.

    有很多認知智商, 卻沒有情緒智商。

  • So that got me thinking,

    所以這讓我思考,

  • what if our technology could sense our emotions?

    如果我們的科技可以 感受我們的情緒會怎樣?

  • What if our devices could sense how we felt and reacted accordingly,

    如果我們的電子裝置可以 感受我們的感覺並做出相對回應,

  • just the way an emotionally intelligent friend would?

    就像一位高情商的朋友一樣, 會是怎樣?

  • Those questions led me and my team

    這些問題讓我及我的團隊

  • to create technologies that can read and respond to our emotions,

    創造出可以讀懂情緒 並做出回應的科技,

  • and our starting point was the human face.

    我們的起始點是人的臉。

  • So our human face happens to be one of the most powerful channels

    人類的臉恰好就是有力的管道,

  • that we all use to communicate social and emotional states,

    能用來傳遞社交及情緒狀態,

  • everything from enjoyment, surprise,

    從愉快、驚訝,

  • empathy and curiosity.

    到同情、好奇都可以。

  • In emotion science, we call each facial muscle movement an action unit.

    情緒科學中,我們稱每一種 顏面肌肉運動為一個動作單位。

  • So for example, action unit 12,

    舉例來說,動作單位 12,

  • it's not a Hollywood blockbuster,

    這可不是好萊塢的動作巨片,

  • it is actually a lip corner pull, which is the main component of a smile.

    這其實是拉嘴角, 這是微笑的主要部分。

  • Try it everybody. Let's get some smiles going on.

    大家都試一下吧! 讓會場有點笑容。

  • Another example is action unit 4. It's the brow furrow.

    另一個例子是動作單位 4。 這是蹙額。

  • It's when you draw your eyebrows together

    就是你把眉頭皺在一起

  • and you create all these textures and wrinkles.

    所產生的紋理和皺紋。

  • We don't like them, but it's a strong indicator of a negative emotion.

    我們都不喜歡皺紋, 但那是負面情緒的重要指標。

  • So we have about 45 of these action units,

    我們有約 45 種動作單位,

  • and they combine to express hundreds of emotions.

    排列組合後可以表現出數百種情緒。

  • Teaching a computer to read these facial emotions is hard,

    要教電腦讀懂這些顏面表情很難,

  • because these action units, they can be fast, they're subtle,

    因為這些動作單位很快、很細微,

  • and they combine in many different ways.

    而且還有各種不同的組合法。

  • So take, for example, the smile and the smirk.

    所以再舉個例子,微笑和假笑。

  • They look somewhat similar, but they mean very different things.

    兩者看起來有點像, 但是意義大不相同。

  • (Laughter)

    (笑聲)

  • So the smile is positive,

    微笑是正面的,

  • a smirk is often negative.

    假笑往往是負面的。

  • Sometimes a smirk can make you become famous.

    有時候一個假笑可以讓你成名。

  • But seriously, it's important for a computer to be able

    但是說真的,要讓電腦能夠

  • to tell the difference between the two expressions.

    辨認出這兩種表情的不同很重要。

  • So how do we do that?

    所以我們怎麼做呢?

  • We give our algorithms

    我們給我們的演算法

  • tens of thousands of examples of people we know to be smiling,

    成千上萬筆我們知道在微笑的例子,

  • from different ethnicities, ages, genders,

    各式人種、年齡、性別都有,

  • and we do the same for smirks.

    假笑也如法泡製。

  • And then, using deep learning,

    然後,機器用深度學習法,

  • the algorithm looks for all these textures and wrinkles

    讓演算法找出臉上 所有的紋理、皺紋,

  • and shape changes on our face,

    及臉型的改變,

  • and basically learns that all smiles have common characteristics,

    基本上學得所有的微笑 都有共同的特點,

  • all smirks have subtly different characteristics.

    所有的假笑也有 稍稍不同的特點,

  • And the next time it sees a new face,

    所以下一次電腦看到新的面孔,

  • it essentially learns that

    它基本上會得知

  • this face has the same characteristics of a smile,

    這張臉與微笑有相同的特點,

  • and it says, "Aha, I recognize this. This is a smile expression."

    然後它會說,「啊哈! 我認得這個,這是微笑的表情。」

  • So the best way to demonstrate how this technology works

    要展示怎麼用 這項科技的最佳方法,

  • is to try a live demo,

    就是來一個現場示範,

  • so I need a volunteer, preferably somebody with a face.

    所以我需要一名志願者, 最好是有臉的。

  • (Laughter)

    (笑聲)

  • Cloe's going to be our volunteer today.

    我們今天的志願者是克蘿伊。

  • So over the past five years, we've moved from being a research project at MIT

    過去五年,我們從 麻省理工的一項研究計畫

  • to a company,

    發展成一家公司,

  • where my team has worked really hard to make this technology work,

    我的團隊很努力 讓這項科技能快速傳播,

  • as we like to say, in the wild.

    好像我們常說的,(病毒)擴散中。

  • And we've also shrunk it so that the core emotion engine

    我們也把它縮小, 讓核心情緒引擎能用在

  • works on any mobile device with a camera, like this iPad.

    任何有照相機的行動裝置上, 像是這台 iPad。

  • So let's give this a try.

    現在來試一下。

  • As you can see, the algorithm has essentially found Cloe's face,

    正如你們所見,基本上 演算法已經找到了克蘿伊的臉,

  • so it's this white bounding box,

    就是這個白色的框框,

  • and it's tracking the main feature points on her face,

    它正在找她臉上的 幾個主要特徵點,

  • so her eyebrows, her eyes, her mouth and her nose.

    像是她的眉毛、 眼睛、嘴巴和鼻子。

  • The question is, can it recognize her expression?

    問題是,它能辨識她的表情嗎?

  • So we're going to test the machine.

    我們來考一下機器。

  • So first of all, give me your poker face. Yep, awesome. (Laughter)

    首先,來一張撲克臉。 對,好極了!(笑聲)

  • And then as she smiles, this is a genuine smile, it's great.

    然後她微笑的時後, 這是真誠的微笑,很棒,

  • So you can see the green bar go up as she smiles.

    你們可以看到她微笑的時候, 綠色的信號格增加。

  • Now that was a big smile.

    那可是個好大的微笑。

  • Can you try a subtle smile to see if the computer can recognize?

    你可以試一下淺淺的微笑嗎? 看看電腦能不能辨識?

  • It does recognize subtle smiles as well.

    它的確也能辨識淺淺的微笑。

  • We've worked really hard to make that happen.

    我們真的很努力要做到這一點。

  • And then eyebrow raised, indicator of surprise.

    然後抬眉毛,表示驚訝。

  • Brow furrow, which is an indicator of confusion.

    蹙額,表示困惑。

  • Frown. Yes, perfect.

    皺眉,很好,很完美。

  • So these are all the different action units. There's many more of them.

    這些就是不同的動作單位。 還有更多。

  • This is just a slimmed-down demo.

    這只是瘦身版示範。

  • But we call each reading an emotion data point,

    我們稱每一個讀取 為一個情緒資料點,

  • and then they can fire together to portray different emotions.

    然後它們一起發動 就能描繪出不同的情緒。

  • So on the right side of the demo -- look like you're happy.

    右邊的這張示範── 表現你很開心。

  • So that's joy. Joy fires up.

    所以那是高興。高興出現了。

  • And then give me a disgust face.

    然後給我一張噁心的臉。

  • Try to remember what it was like when Zayn left One Direction.

    試著回想贊恩退出 男團一世代的那種感覺。

  • (Laughter)

    (笑聲)

  • Yeah, wrinkle your nose. Awesome.

    沒錯,皺鼻子。太棒了!

  • And the valence is actually quite negative, so you must have been a big fan.

    效價呈現高負值, 所以你一定是大粉絲。

  • So valence is how positive or negative an experience is,

    效價指的是感受的好壞程度,

  • and engagement is how expressive she is as well.

    而投入程度指的是 她的表情有多大。

  • So imagine if Cloe had access to this real-time emotion stream,

    想像一下如果克羅伊 能使用這套即時情緒串流,

  • and she could share it with anybody she wanted to.

    而且她還可以跟任何人分享。

  • Thank you.

    謝謝妳!

  • (Applause)

    (掌聲)

  • So, so far, we have amassed 12 billion of these emotion data points.

    到目前為止我們已經 累積了 120 億筆情緒數據點。

  • It's the largest emotion database in the world.

    這是世界上最大的情緒資料庫。

  • We've collected it from 2.9 million face videos,

    我們從 290 萬筆臉孔短片 收集資料,

  • people who have agreed to share their emotions with us,

    由同意與我們分享他們情緒的人提供,

  • and from 75 countries around the world.

    來源遍及全球 75 個國家。

  • It's growing every day.

    資料每天都在增加。

  • It blows my mind away

    這真令我驚異萬分,

  • that we can now quantify something as personal as our emotions,

    我們能量化像情緒 這麼個人的東西,

  • and we can do it at this scale.

    還能做到這個地步。

  • So what have we learned to date?

    所以至今我們學到什麼?

  • Gender.

    性別。

  • Our data confirms something that you might suspect.

    我們的數據證實了一些 你們大概已經料到的事。

  • Women are more expressive than men.

    女人的表情比男人的更豐富。

  • Not only do they smile more, their smiles last longer,

    她們不但更常微笑, 微笑的時間還更久,

  • and we can now really quantify what it is that men and women

    而且我們現在真的能量化

  • respond to differently.

    造成男女不同反應的東西。

  • Let's do culture: So in the United States,

    來看文化:在美國,

  • women are 40 percent more expressive than men,

    女性比男性多 40% 更願意表達情感,

  • but curiously, we don't see any difference in the U.K. between men and women.

    但奇怪的是, 在英國看不到這樣的差距。

  • (Laughter)

    (笑聲)

  • Age: People who are 50 years and older

    再看年齡:50 歲以上的人

  • are 25 percent more emotive than younger people.

    比年輕人多 25% 更願意表現情感。

  • Women in their 20s smile a lot more than men the same age,

    20 多歲的女性 比同年齡的男性更常微笑,

  • perhaps a necessity for dating.

    大概是因為這是約會必殺技。

  • But perhaps what surprised us the most about this data

    但是這筆數據最讓我們訝異的,

  • is that we happen to be expressive all the time,

    大概是我們隨時都有表情,

  • even when we are sitting in front of our devices alone,

    即使我們獨自坐在裝置前也是如此,

  • and it's not just when we're watching cat videos on Facebook.

    而且不只是在我們看 臉書上貓短片的的時候。

  • We are expressive when we're emailing, texting, shopping online,

    我們在寫信、傳簡訊、網購,

  • or even doing our taxes.

    甚至在報稅時都表情豐富。

  • Where is this data used today?

    今天這筆數據用在哪裡呢?

  • In understanding how we engage with media,

    用在瞭解我們如何與媒體互動,

  • so understanding virality and voting behavior;

    所以能瞭解影片爆紅及投票行為,

  • and also empowering or emotion-enabling technology,

    也用在情緒辨識科技,

  • and I want to share some examples that are especially close to my heart.

    我想分享幾個 讓我特別感動的例子。

  • Emotion-enabled wearable glasses can help individuals

    情緒辨識眼鏡能幫助

  • who are visually impaired read the faces of others,

    視障者讀取別人臉上的表情,

  • and it can help individuals on the autism spectrum interpret emotion,

    也能幫助各種程度的 自閉症患者解讀情緒,

  • something that they really struggle with.

    這是他們的最大難題。

  • In education, imagine if your learning apps

    在教育上,想像一下 如果你的學習應用程式

  • sense that you're confused and slow down,

    感受到你的困惑並放慢速度,

  • or that you're bored, so it's sped up,

    或是知道你覺得無聊了 所以加快速度,

  • just like a great teacher would in a classroom.

    就像一位好老師 在課堂上做的一樣。

  • What if your wristwatch tracked your mood,

    如果你的手錶能追蹤你的心情,

  • or your car sensed that you're tired,

    或是你的車能感受到 你現在很疲倦,

  • or perhaps your fridge knows that you're stressed,

    或是你的冰箱能知道 你現在壓力很大,

  • so it auto-locks to prevent you from binge eating. (Laughter)

    所以它會自動鎖住, 你就不能拿東西來吃。(笑聲)

  • I would like that, yeah.

    我會喜歡那個,真的。

  • What if, when I was in Cambridge,

    當我在劍橋的時候,

  • I had access to my real-time emotion stream,

    如果我能用這套 即時情緒串流工具,

  • and I could share that with my family back home in a very natural way,

    我就能用非常自然的方法 與遠在家鄉的家人分享,

  • just like I would've if we were all in the same room together?

    就好像我們都在 同一間房間一樣,那有多好?

  • I think five years down the line,

    我想五年後,

  • all our devices are going to have an emotion chip,

    我們所有的裝置 都會有一個情緒晶片,

  • and we won't remember what it was like when we couldn't just frown at our device

    我們就會忘記當年 裝置還不會回應我們皺眉的時候說出:

  • and our device would say, "Hmm, you didn't like that, did you?"

    「嗯,你不喜歡這個,是吧?」 是什麼樣子。

  • Our biggest challenge is that there are so many applications of this technology,

    我們最大的挑戰是 這種科技有許多應用程式,

  • my team and I realize that we can't build them all ourselves,

    我和我的團隊瞭解 我們不可能只靠自己發展全部,

  • so we've made this technology available so that other developers

    所以我們開放這項科技 讓其他開發者

  • can get building and get creative.

    能繼續開發並激發創意。

  • We recognize that there are potential risks

    我們知道會有潛在風險,

  • and potential for abuse,

    也可能遭到濫用,

  • but personally, having spent many years doing this,

    但是個人認為, 在花了這麼多年做這個之後,

  • I believe that the benefits to humanity

    我相信這對人類的益處,

  • from having emotionally intelligent technology

    就是開發情緒智能科技的益處,

  • far outweigh the potential for misuse.

    遠超過誤用的潛在危險。

  • And I invite you all to be part of the conversation.

    我請大家口耳相傳。

  • The more people who know about this technology,

    愈多人知道這項科技,

  • the more we can all have a voice in how it's being used.

    我們就愈能發聲說明 這該如何使用。

  • So as more and more of our lives become digital,

    隨著我們的生活愈來愈數位化,

  • we are fighting a losing battle trying to curb our usage of devices

    試圖以遏止使用裝置來重拾情緒

  • in order to reclaim our emotions.

    是一場必敗的仗。

  • So what I'm trying to do instead is to bring emotions into our technology

    與其如此, 我寧可把情感帶進科技,

  • and make our technologies more responsive.

    讓我們的科技更有回應。

  • So I want those devices that have separated us

    所以我想用這些 原本使我們疏遠的裝置,

  • to bring us back together.

    讓我們重新結合在一起。

  • And by humanizing technology, we have this golden opportunity

    藉著把科技人性化, 我們擁有這個黃金時機

  • to reimagine how we connect with machines,

    來重新想像我們如何 與機器連結,

  • and therefore, how we, as human beings,

    進而想像我們身為人類

  • connect with one another.

    如何能重新連結彼此。

  • Thank you.

    謝謝。

  • (Applause)

    (掌聲)

Our emotions influence every aspect of our lives,

我們的情緒會影響 日常生活的各個層面,

字幕與單字

B1 中級 中文 美國腔 情緒 科技 表情 假笑 裝置 單位

【TED】這個應用程式知道你的感覺—從你的表情就知道了!Rana el Kaliouby: This app knows how you feel — from the look on your face

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    CUChou   發佈於 2015 年 07 月 13 日
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