Fake smiles and the computers that can spot them - 6 Minute English
ฝัง
- เผยแพร่เมื่อ 18 ก.ย. 2019
- Sometimes it can be difficult to tell if someone is really smiling or the smirk on their face is fake. But now there are computers that are able tell real smiles from fake ones better than humans can. How do they work and what are the benefits? It's something Neil and Sam are discussing in 6 Minute English as well as teaching you some useful vocabulary that will hopefully bring a smile to your face.
To download a transcript and audio, go here: www.bbc.co.uk/learningenglish/...
𝐌𝐨𝐫𝐞 𝐞𝐩𝐢𝐬𝐨𝐝𝐞𝐬:
The art of tipping
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The future of food
• The future of food - 6...
𝐕𝐨𝐜𝐚𝐛𝐮𝐥𝐚𝐫𝐲:
𝐟𝐚𝐜𝐢𝐚𝐥
adjective to do with the face
𝐭𝐨 𝐢𝐧𝐟𝐞𝐫
to come to a decision about something using the information you have, which may not be complete
𝐢𝐧 𝐫𝐞𝐚𝐥 𝐭𝐢𝐦𝐞
at the same time as, without delay
𝐭𝐨 𝐢𝐧𝐝𝐮𝐜𝐞
to cause something to happen
𝐠𝐞𝐧𝐮𝐢𝐧𝐞
real, not fake
𝐭𝐨 𝐟𝐢𝐠𝐮𝐫𝐞 𝐨𝐮𝐭
to calculate, to work out
[Cover images: Getty Images]
#BBCLearningEnglish #6MinuteEnglish #LearnEnglish
Learn an English phrase to make you smile! th-cam.com/video/Qn0FeE2FVSc/w-d-xo.html
Why don't you guys show your face ?
Is it a radio channel or what? Why can't I see your facial expressions or the way you speak ?
1. FACIAL muscle movement => Adjective of FACE.
2. In real time = at the same time, without delay.
=> Eg: Looking at someone' s face IN REAL TIME.
3. Genuine smile= Real smile.
4. To induce: to cause something to happen.
=> To INDUCE genuine smiles in the lab.
5. To infer the emotions: To understand something without being told directly.
BBC learning English Thanks for helping us to learn this language
I am genuinely grateful for all your online lessons. Thank you!
Hi 🙋🏼♀️
It’s an useful vocabularies , thanks a lot
Neil you’ve answered “ 42” but in the choices there are “ 26 ‘ 43 ‘ 62 “ concerning the question “ How many muscles do we have in our face ? “ !!🤔
Thanks and well spotted. Neil gave out the wrong answer - it should be 43. I bet you've got a real smile on your face now!
BBC Learning English
Haha exactly , yes I have 😀
BBC Learning English
Haha exactly , yes I have 😀
BBC Learning English
Haha exactly , yes I have 😀
Thanks for these information .
I’m really appreciate the huge effort to make this show thanks 🙏 from Iraq 🇮🇶
Thank you, BBC. 💚
Thank you so much ..
Thank you Neil and Sam👀🥳
Lovely!
Hello from London! You've made us smile (a genuine smile)! 😊
@@bbclearningenglish I'm so excited that you replied my comment! Thank you very much😊🌍📻
@@bbclearningenglish Another greetings from Poland, this time from Bielsko-Biała
Thank you so much :D
Plz talk a about one historical period such as victorian
Hi BBC. Could you check your video's description? I think option B is a typo. Cheers
Thanks for letting us know. Neil should have said the answer was option B, 43 not 42.
Cool!
Note: There are some verbs that we don’t usually use in the continuous form. They are often verbs of thinking and feeling, for example: hear, see, smell, hate, know, understand, believe, want, need.
WRONG: Could you explain that again? I’m not understanding.
CORRECT: Could you explain that again? I don’t understand.
Today: To infer something means to get an understanding of something without actually being told directly. So, you look at available information and use your understanding and knowledge to work out the meaning.
Why are you using "understanding"? Is it correct? Please explain.
Regards
correct. because it is a noun. not verb
I'm smiling now, it's a genuine smile
Hi, I think genuine smile requires more muscles, so it's easy for computers to determine what kind of smile it is by calculating how many muscles moves each time.
Anyway, I think computers can be tricked by people when they know how this method works.
This program is somehow similar to the program that can distinguish between a lier and a one telling the truth by measuring the level of the adrenaline releasing when someone is being asked , which also was tricked.
I'm sure we can fool computers some of the time!
I think sometimes fakes smiles requires more muscles, because, when we are making a fake smile, it's a kind of effort.
@@thenightbringer9770 anyway, the number of muscles are different.
The weird smile of the guy in mustard shirt just scared me out of my wits
The brand induced a genuine promotion to attract the customers.
Neil: Hello. This is 6 Minute English, I'm Neil.
Sam: And I'm Sam.
Neil: It’s good to see you again, Sam
Sam: Really?
Neil: Yes, of course, can’t you tell by the
way I’m smiling?
Sam: Ah well, I find it difficult to tell if
someone is really smiling or if it’s a fake
smile.
Neil: Well, that’s a coincidence because
this programme is all about how
computers may be able tell real smiles
from fake smiles better than humans can.
Before we get in to that though, a
question. The expressions we can
make with our face are controlled by
muscles. How many muscles do we have
in our face? Is it:
A: 26, B: 43 or C: 62?
What do you think, Sam?
Sam: No idea! But a lot, I’d guess, so I’m
going with 62.
Neil: OK. Well, we’ll see if you’ll be smiling
or crying later in the programme.
Hassan Ugail is a professor of visual
computing at the University of Bradford.
He’s been working on getting computers
to be able to recognise human emotions
from the expressions on our
face. Here he is speaking on the BBC
Inside Science radio programme - how
successful does he say they have been?
Professor Hassan Ugail: We've been
working quite a lot on the human
emotions, so the idea is how the facial
muscle movement, which is reflected on
the face, through obviously a computer
through video frames and trying to
understand how these muscle
movements actually relate to facial
expressions and then from facial
expressions trying to understand the
emotions or to infer the emotions. And
they have been quite successful
in doing that. We have software that can
actually look at somebody's face in real
time and then identify the series of
emotions that person
is expressing in real time as well.
Neil: So, have they been successful in
getting computers to identify emotions?
Sam: Yes, he says they’ve been quite
successful, and what’s interesting is that
he says that the computers can do it in
'real time'. This means that there’s no
delay. They don’t have to stop and analyse
the data, or crunch the numbers, they can
do it as the person is talking.
Neil: The system uses video to analyse a
person’s expressions and can then infer
the emotions.
'To infer something' means to get an
understanding of something without
actually being told directly.
So, you look at available information and
use your understanding and knowledge to
work out the meaning.
Sam: It’s a bit like being a detective, isn’t
it? You look at the clues and infer what
happened even if you don’t have all the
details.
Neil: Yes, and in this case the computer
looks at how the movement of muscles in
the face or 'facial muscles', show different
emotions. Here’s Professor Ugail again.
Professor Hassan Ugail: We've been
working quite a lot on the human
emotions so the idea is how the facial
muscle movement, which is reflected on
the face, through obviously a computer
through video frames and trying to
understand how these
muscle movements actually relate to
facial expressions and then from facial
expressions trying to understand the
emotions or to infer the emotions. And
they have been quite successful
in doing that. We have software that can
actually look at somebody's face in real
time and then identify the series of
emotions that person is expressing in real
time as well.
Neil: So, how do the computers know
what is a real or a fake smile? The
computers have to learn
that first. Here’s Professor Ugail again
talking about how they do that.
Professor Hassan Ugail: We have a data
set of real smiles and we have
a data set of fake smiles. These real
smiles are induced smiles in a lab. So,
you put somebody on a chair and then
show some funny movies
and we expect the smiles are genuine
smiles.
And similarly we ask them to pretend to
smile. So, these are what you'd call fake
smiles.
So, what we do is we throw these into the
machine and then the machine figures
out what are the characteristics of a real
smile and what are the characteristics of
a fake smile.
Neil: So, how do they get the data that the
computers use to see if your smile is fake
or 'genuine' - which is another word which
means real?
Sam: They induce real smiles in the lab by
showing people funny films. This means
that they make the smiles come naturally.
They assume that the smiles while
watching the funny films are genuine.
Neil: And then they ask the people to
pretend to smile and the computer
programme now has a database of real
and fake smiles and is able
to figure out which is which.
Sam: 'Figure out' means to calculate and
come to an answer
Neil: Yes, and apparently the system gets
it right 90% of the time, which is much
higher than we humans can. Right, well
before we remind ourselves of our
vocabulary, let’s get the answer to the
question. How many muscles do
we have in our face? Is it:
A: 26, B: 43 or C: 62.
Sam, are you going to be smiling?
What did you say?
Sam: So I thought 62! Am I smiling, Neil?
Neil: Sadly you are not, you are using
different muscles for that sort of sad
look! Actually the answer is 43.
Congratulations to anyone
who got that right. Now our vocabulary.
Sam: Yes - 'facial' is the adjective relating
to face.
Neil: Then we had 'infer'. This verb means
to understand something even when you
don’t have all the information, and you
come to this understanding
based on your experience and knowledge,
or in the case of a computer, the
programming.
Sam: And these computers work in 'real
time', which means that there’s no delay
and they can tell a fake smile from a
'genuine' one, which means a real one, as
the person is speaking.
Neil: They made people smile, or as the
Professor said, they 'induced' smiles by
showing funny films.
Sam: And the computer is able to 'figure
out', or calculate, whether the smile is fake
or genuine.
Neil: OK, thank you, Sam. That’s all from
6 Minute English today. We look forward
to your company next time and if you
can’t wait you can find lots more from
bbclearningenglish online,
on social media and on our app. Goodbye!
Sam: Bye!
Hardworkkkk
Mr. Ugail's speech is grammatically correct?
هل القناة سوف تستمر وإلى متى
no smile in life.. :-(
Transcript
Note: This is not a word for word transcript
Neil
Hello. This is 6 Minute English, I'm Neil.
Sam
And I'm Sam.
Neil
It’s good to see you again, Sam.
Sam
Really?
Neil
Yes, of course, can’t you tell by the way I’m smiling?
Sam
Ah well, I find it difficult to tell if someone is really smiling or if it’s a fake smile.
Neil
Well, that’s a coincidence because today’s programme is all about how computers may be able tell real smiles from fake smiles better than humans can. Before we get in to that though, a question. The expressions we can make with our face are controlled by muscles. How many muscles do we have in our face? Is it:
A: 26
B: 43
C: 62
What do you think, Sam?
Sam
No idea! But a lot, I’d guess, so I’m going with 62.
Neil
OK. Well, we’ll see if you’ll be smiling or crying later in the programme. Hassan Ugail is a professor of visual computing at the University of Bradford. He’s been working on getting computers to be able to recognise human emotions from the expressions on our face. Here he is speaking on the BBC Inside Science radio programme - how successful does he say they have been?
Professor Hassan Ugail
We've been working quite a lot on the human emotions, so the idea is how the facial muscle movement, which is reflected on the face, through obviously a computer through video frames and trying to understand how these muscle movements actually relate to facial expressions and then from facial expressions trying to understand the emotions or to infer the emotions. And they have been quite successful in doing that. We have software that can actually look at somebody's face in real time and then identify the series of emotions that person is expressing in real time as well.
Neil
So, have they been successful in getting computers to identify emotions?
Sam
Yes, he says they’ve been quite successful, and what’s interesting is that he says that the computers can do it in real time. This means that there’s no delay. They don’t have to stop and analyse the data, or crunch the numbers, they can do it as the person is talking.
Neil
The system uses video to analyse a person’s expressions and can then infer the emotions. To infer something means to get an understanding of something without actually being told directly. So, you look at available information and use your understanding and knowledge to work out the meaning.
Sam
It’s a bit like being a detective, isn’t it? You look at the clues and infer what happened even if you don’t have all the details.
Neil
Yes, and in this case the computer looks at how the movement of muscles in the face or facial muscles, show different emotions. Here’s Professor Ugail again.
Professor Hassan Ugail
We've been working quite a lot on the human emotions so the idea is how the facial muscle movement, which is reflected on the face, through obviously a computer through video frames and trying to understand how these muscle movements actually relate to facial expressions and then from facial expressions trying to understand the emotions or to infer the emotions. And they have been quite successful in doing that. We have software that can actually look at somebody's face in real time and then identify the series of emotions that person is expressing in real time as well.
Neil
So, how do the computers know what is a real or a fake smile? The computers have to learn that first. Here’s Professor Ugail again talking about how they do that.
Professor Hassan Ugail
We have a data set of real smiles and we have a data set of fake smiles. These real smiles are induced smiles in a lab. So, you put somebody on a chair and then show some funny movies and we expect the smiles are genuine smiles. And similarly we ask them to pretend to smile. So, these are what you'd call fake smiles. So, what we do is we throw these into the machine and then the machine figures out what are the characteristics of a real smile and what are the characteristics of a fake smile.
Neil
So, how do they get the data that the computers use to see if your smile is fake or genuine - which is another word which means real?
Sam
They induce real smiles in the lab by showing people funny films. This means that they make the smiles come naturally. They assume that the smiles while watching the funny films are genuine.
Neil
And then they ask the people to pretend to smile and the computer programme now has a database of real and fake smiles and is able to figure out which is which.
Sam
Figure out means to calculate and come to an answer
Neil
Yes, and apparently the system gets it right 90% of the time, which is much higher than we humans can. Right, well before we remind ourselves of our vocabulary, let’s get the answer to the question. How many muscles do we have in our face? Is it:
A: 26
B: 43
C: 62
Sam, are you going to be smiling? What did you say?
Sam
So I thought 62! Am I smiling, Neil?
Neil
Sadly you are not, you are using different muscles for that sort of sad look! Actually the answer is 43. Congratulations to anyone who got that right. Now our vocabulary.
Sam
Yes - facial is the adjective relating to face.
Neil
Then we had infer. This verb means to understand something even when you don’t have all the information, and you come to this understanding based on your experience and knowledge, or in the case of a computer, the programming.
Sam
And these computers work in real time, which means that there’s no delay and they can tell a fake smile from a genuine one, which means a real one, as the person is speaking.
Neil
They made people smile, or as the Professor said, they induced smiles by showing funny films.
Sam
And the computer is able to figure out or calculate whether the smile is fake or genuine.
Neil
OK, thank you, Sam. That’s all from 6 Minute English today. We look forward to your company next time and if you can’t wait you can find lots more from bbclearningenglish online, on social media and on our app. Goodbye!
Sam
Bye!
Actually the answer is 43 or 42? Neil said 42 when he informed the answer of today's Quiz, didn't he?
Yes! He admits he made a mistake - the answer was b) 43. Big smiles all round!
@@bbclearningenglish I'm very proud of being able to notice that. Finally I can say my English is improving, isn't it?
:D :D :D :D
second 😀
Second comment
First comment
Nice video sir... फिल्मो से इंग्लिश सिखने के लिए यहा क्लिक करे
The professor sounds like have an accent
Plz bring back Alice. She is the best, I don't like Sam.
That's pretty rude
@@TheFlowerbeastNo offense, I just expressed my feeling frankly.
@@charlchen5297 You could have worded your request respectfully. One of the fundamentals in the English language is politeness.