Fake smiles and the computers that can spot them - 6 Minute English

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!