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THEY SING | 0:00:02 | 0:00:03 | |
Lovely, isn't it? Very, very beautiful, you know. | 0:00:03 | 0:00:06 | |
Stirs the heart. I mean, they're just warming up. | 0:00:06 | 0:00:08 | |
It's actually not a tune or anything, | 0:00:08 | 0:00:10 | |
so I suppose it's not music, but it's musical, so maybe that is... | 0:00:10 | 0:00:13 | |
And it creates an emotional response... | 0:00:13 | 0:00:15 | |
I mean, music is a real puzzle. I mean, what is it exactly? | 0:00:15 | 0:00:18 | |
We do like a puzzle here, don't we? | 0:00:18 | 0:00:20 | |
I'm Dara O'Briain, welcome to Science Club. | 0:00:20 | 0:00:23 | |
CHEERING AND APPLAUSE | 0:00:23 | 0:00:25 | |
Yes, here, in Science Club, we take one topic | 0:00:49 | 0:00:53 | |
and we explore it from a variety of different perspectives. | 0:00:53 | 0:00:55 | |
Lighting up the dark, recesses of understanding. | 0:00:55 | 0:00:57 | |
Again, we're joined by our curious audience and our illustrious guests, | 0:00:57 | 0:01:01 | |
Acoustics expert Professor Trevor Cox, thank you very much. | 0:01:01 | 0:01:03 | |
Music psychologist Dr Alexandra Lamont, thank you for coming in. | 0:01:03 | 0:01:07 | |
Our reporters are here. | 0:01:07 | 0:01:08 | |
Science reporter Alok Jha and Dr Tali Sharot | 0:01:08 | 0:01:10 | |
and James May, you're with us later too, aren't you? | 0:01:10 | 0:01:12 | |
-Absolutely, yes. -Great, looking forward to seeing more about it. | 0:01:12 | 0:01:15 | |
And materials scientist Professor Mark Miodownik will be doing some experiments. | 0:01:15 | 0:01:19 | |
On the show tonight, we're looking at music. | 0:01:19 | 0:01:21 | |
It's everywhere in our world. | 0:01:21 | 0:01:23 | |
In fact, every human culture has music at its centre. | 0:01:23 | 0:01:26 | |
But what is music? What is it so important to us? | 0:01:26 | 0:01:28 | |
And how does it interact with our brains? On tonight's show... | 0:01:28 | 0:01:32 | |
Dr Tali Sharot travels to the US to investigate a rhythm therapy | 0:01:35 | 0:01:39 | |
that reveals a startling connection between hearing and movement. | 0:01:39 | 0:01:43 | |
Journalist Alok Jha looks into music technology | 0:01:43 | 0:01:45 | |
and asks whether computers are ruining music. | 0:01:45 | 0:01:48 | |
And who knew, Top Gear's James May originally studied as a musician. | 0:01:48 | 0:01:52 | |
Here, he discovers that his brain's response to music | 0:01:52 | 0:01:55 | |
is stronger than he might have imagined. | 0:01:55 | 0:01:57 | |
-So my brain is present. -Oh, yeah. -That's reassuring. | 0:01:57 | 0:02:01 | |
-Beautiful. -Thank you. -This experiment apparently really worked. | 0:02:01 | 0:02:04 | |
If you want to get involved in the show or follow us on Twitter, | 0:02:04 | 0:02:07 | |
the details are on your screen. | 0:02:07 | 0:02:09 | |
So first, let's meet this week's science gurus. | 0:02:12 | 0:02:15 | |
Professor of Acoustic Engineering at the University of Salford | 0:02:15 | 0:02:18 | |
and former President of the Institute of Acoustics, Professor Trevor Cox | 0:02:18 | 0:02:22 | |
and Senior Lecturer in Music Psychology at Keele University, | 0:02:22 | 0:02:25 | |
Dr Alexandra Lamont. Thank you very much. | 0:02:25 | 0:02:27 | |
CHEERING AND APPLAUSE | 0:02:27 | 0:02:28 | |
How are you? Thank you for coming in. | 0:02:33 | 0:02:35 | |
Hi, how are you? Thank you for coming in. | 0:02:35 | 0:02:38 | |
Can I ask you the straight question that I've already... It's going to run through the whole show. | 0:02:38 | 0:02:42 | |
What is music? | 0:02:42 | 0:02:43 | |
I'd say something that promotes some form of emotional response in the listener. | 0:02:43 | 0:02:46 | |
But music can be loads of things. I went to see John Cage's Four Minutes, Thirty-three Seconds, | 0:02:46 | 0:02:50 | |
-his famous silent work. -You went to see an entirely silent work? | 0:02:50 | 0:02:54 | |
I did indeed and my kid couldn't believe that I was spending ten quid to go and sit in silence. | 0:02:54 | 0:02:58 | |
What? You spent money and sat in silence for four minutes and 33 seconds of complete silence. | 0:02:58 | 0:03:02 | |
-And it was a great piece of music. -Was it a good performance of it? | 0:03:02 | 0:03:06 | |
LAUGHTER | 0:03:06 | 0:03:08 | |
Have you seen it more than once? | 0:03:08 | 0:03:10 | |
No, I've only seen it once | 0:03:10 | 0:03:11 | |
and this was a particular arrangement for three pianists. | 0:03:11 | 0:03:14 | |
-Oh... -Yeah, it's much better than the solo version. -Yes, I get that. | 0:03:14 | 0:03:18 | |
But, psychologically, I mean, we've already gone straight to emotion, | 0:03:18 | 0:03:21 | |
we skipped through the science entirely. | 0:03:21 | 0:03:23 | |
Yeah, that's great, cos that's what I'm interested in. | 0:03:23 | 0:03:25 | |
OK, fine. But still, you know, I mean, | 0:03:25 | 0:03:28 | |
cos, an acoustic expert, we may regard you as reductionist to a certain extent, | 0:03:28 | 0:03:32 | |
you may now go down to the waves and frequencies and all that. | 0:03:32 | 0:03:34 | |
You're dealing with its effect on the brain... | 0:03:34 | 0:03:37 | |
Yeah, I would have actually said music is organised sounds, | 0:03:37 | 0:03:39 | |
so it's interesting you've come with the emotional explanation | 0:03:39 | 0:03:42 | |
and I've come up with the more acoustic one. | 0:03:42 | 0:03:44 | |
But I think music is something that makes us respond. | 0:03:44 | 0:03:46 | |
Music is something that every human culture has | 0:03:46 | 0:03:49 | |
and it doesn't matter how good we are at it, we can still respond to it. | 0:03:49 | 0:03:52 | |
So I think it's an essential part of being human. | 0:03:52 | 0:03:54 | |
By the way, does it exist in any animals at all? | 0:03:54 | 0:03:57 | |
That's an interesting question. There's a bit of research on this showing... | 0:03:57 | 0:04:00 | |
I mean, songs...you know, birds, for example, communicate through song. | 0:04:00 | 0:04:04 | |
But most of that is strategic and symbolic and it's about messages. | 0:04:04 | 0:04:07 | |
It's not for fun, it's not for pleasure. | 0:04:07 | 0:04:09 | |
It's not for the enjoyment and the aesthetic evaluation of, yeah, | 0:04:09 | 0:04:13 | |
it's a different kind of thing. | 0:04:13 | 0:04:14 | |
So there are elements of non-human sounds that you could think of as being a little bit like music, | 0:04:14 | 0:04:20 | |
-but they don't work like music does for humans. -OK, fine. | 0:04:20 | 0:04:23 | |
Well, we're going to explore these issues more as the show goes on. | 0:04:23 | 0:04:26 | |
But even though there're maybe different opinions | 0:04:26 | 0:04:28 | |
in terms of how we would define it, | 0:04:28 | 0:04:30 | |
yes, it is a universal cultural trait common to all human societies | 0:04:30 | 0:04:33 | |
and it has been for a very long time. | 0:04:33 | 0:04:36 | |
How did music begin? No-one knows. | 0:04:40 | 0:04:42 | |
But humans have been making music for a very long time. | 0:04:42 | 0:04:46 | |
Perhaps even longer than we've had language. | 0:04:46 | 0:04:49 | |
There is evidence of our caveman ancestors | 0:04:49 | 0:04:52 | |
fashioning crude flutes from bear's femurs. | 0:04:52 | 0:04:55 | |
And by 7,000 BC, in China, | 0:04:55 | 0:04:58 | |
we find the first evidence of a melodic flute | 0:04:58 | 0:05:00 | |
that could play a scale and carry a simple tune. | 0:05:00 | 0:05:03 | |
Melodies are made by playing notes one after the other. | 0:05:03 | 0:05:07 | |
Play two at the same time | 0:05:07 | 0:05:08 | |
and you can make harmony - | 0:05:08 | 0:05:10 | |
notes that sound good together. | 0:05:10 | 0:05:12 | |
The story goes that it was Pythagoras | 0:05:12 | 0:05:14 | |
who first worked out why this happens. | 0:05:14 | 0:05:17 | |
Walking past a blacksmith's, | 0:05:17 | 0:05:18 | |
he heard the ring of hammers hitting iron and did some quick sums. | 0:05:18 | 0:05:22 | |
He reckoned whether the hammers sounded good or bad | 0:05:22 | 0:05:24 | |
was down to maths - | 0:05:24 | 0:05:26 | |
if one was half, two thirds or three-quarters | 0:05:26 | 0:05:29 | |
the weight of the other. | 0:05:29 | 0:05:30 | |
Which might be nonsense. | 0:05:30 | 0:05:32 | |
But he was right that maths and harmony are closely related. | 0:05:32 | 0:05:36 | |
Other great minds of science also studied sound and music. | 0:05:38 | 0:05:42 | |
From Aristotle to Leonardo da Vinci and Galileo. | 0:05:42 | 0:05:46 | |
None, however, are particularly noted for their musical prowess. | 0:05:46 | 0:05:49 | |
By now, music had spread - | 0:05:50 | 0:05:52 | |
from blacksmith's forges to medieval monasteries | 0:05:52 | 0:05:56 | |
and then, into houses and courts, | 0:05:56 | 0:05:58 | |
where Renaissance nobles danced to the latest sounds | 0:05:58 | 0:06:00 | |
of the sackbut and crumhorn. | 0:06:00 | 0:06:02 | |
By Beethoven's heyday, | 0:06:04 | 0:06:05 | |
performances had gone from quartets and quintets | 0:06:05 | 0:06:08 | |
to full-blown orchestras. | 0:06:08 | 0:06:10 | |
Not only were there now trombones on top of the triangles and timpani. | 0:06:10 | 0:06:14 | |
But the orchestra had outgrown private houses. | 0:06:14 | 0:06:17 | |
And music was also going commercial. | 0:06:17 | 0:06:20 | |
At the end of his life, | 0:06:20 | 0:06:21 | |
all of Beethoven's symphonies were performed in public concert halls. | 0:06:21 | 0:06:25 | |
Then, one morning in December 1877, | 0:06:28 | 0:06:31 | |
Thomas Edison walked into an office and put a machine on the desk. | 0:06:31 | 0:06:34 | |
He'd made the first device to record and play back sound - | 0:06:34 | 0:06:38 | |
the phonograph. | 0:06:38 | 0:06:39 | |
By introducing technology, | 0:06:39 | 0:06:41 | |
he'd single-handedly kick-started the music industry we know today. | 0:06:41 | 0:06:45 | |
Soon, musical records went on sale. | 0:06:50 | 0:06:53 | |
And then, on Christmas Eve 1906, came the first radio broadcast, | 0:06:53 | 0:06:57 | |
which included a festive Christmas carol. | 0:06:57 | 0:07:00 | |
It was a humble start to music radio. | 0:07:00 | 0:07:02 | |
Music no longer had to be performed live - | 0:07:07 | 0:07:10 | |
you no longer needed an orchestra in your front room. | 0:07:10 | 0:07:12 | |
Thanks to technology, music got smaller, cheaper and louder. | 0:07:12 | 0:07:17 | |
The phonograph, the gramophone, the juke box, the LP, | 0:07:19 | 0:07:23 | |
the Walkman, the CD, the minidisc player and the mp3 | 0:07:23 | 0:07:27 | |
have all brought music to our ears. | 0:07:27 | 0:07:29 | |
Sadly, while technology might allow music to be widely available, | 0:07:31 | 0:07:34 | |
it has no control over the quality of the music produced. | 0:07:34 | 0:07:38 | |
By the way, just to briefly say, over the course of the series, | 0:07:43 | 0:07:46 | |
we've had a lot of feedback from the audience | 0:07:46 | 0:07:48 | |
about those animated histories, | 0:07:48 | 0:07:50 | |
people are very fond of them. | 0:07:50 | 0:07:51 | |
Stills are now downloadable as wallpaper for your computer | 0:07:51 | 0:07:54 | |
if you just go to our website. | 0:07:54 | 0:07:56 | |
Now, did we evolve music? Does it even have an evolutionary purpose? | 0:07:56 | 0:08:01 | |
-Well, it's something we can debate. We don't know for sure. -Yeah. | 0:08:01 | 0:08:04 | |
It might be, for example, a sexual display. | 0:08:04 | 0:08:06 | |
You know, your prowess at making music | 0:08:06 | 0:08:08 | |
may make you a more favourable mate. | 0:08:08 | 0:08:10 | |
And as a society, would we have bonded through music? | 0:08:10 | 0:08:13 | |
I think that's one of the really powerful parts of music, that it brings people together. | 0:08:13 | 0:08:17 | |
So the ability to be in time with somebody, to be in tune with somebody | 0:08:17 | 0:08:20 | |
and to be getting into those sort of synchronised patterns. | 0:08:20 | 0:08:23 | |
I think that's probably a very, very powerful aspect of it. | 0:08:23 | 0:08:26 | |
Actually, if you look at early speech, | 0:08:26 | 0:08:28 | |
when the mother talks to her baby, | 0:08:28 | 0:08:29 | |
and comforts it or teaches it language, | 0:08:29 | 0:08:32 | |
she'll often do it with a singsong while doing it, | 0:08:32 | 0:08:34 | |
so I think it has helped to learning languages as well. So maybe that's the secret. | 0:08:34 | 0:08:38 | |
Do you find, as an acoustic expert, do you find going to gigs | 0:08:38 | 0:08:41 | |
and just being angry about how badly tuned...? | 0:08:41 | 0:08:44 | |
THEY CHUCKLE | 0:08:44 | 0:08:46 | |
I try and enjoy it. | 0:08:46 | 0:08:47 | |
I went to the proms, actually, with a bunch of acoustic experts, auditorium acoustics, | 0:08:47 | 0:08:51 | |
and they all came out whingeing about the acoustics | 0:08:51 | 0:08:53 | |
and I came out saying, "That was a great gig." Cos I just enjoyed it. | 0:08:53 | 0:08:56 | |
We were discussing various instruments. | 0:08:56 | 0:08:58 | |
In terms of sounds that complement each other, | 0:08:58 | 0:09:02 | |
and that's been a large part of how music has evolved. | 0:09:02 | 0:09:04 | |
Yeah, I mean, it's also economically driven, you know. | 0:09:04 | 0:09:07 | |
In the 20th century is about how many people can get in a concert hall | 0:09:07 | 0:09:09 | |
and still have decent acoustics. | 0:09:09 | 0:09:11 | |
When you get a classical orchestra, cos you need to make the orchestra economic. | 0:09:11 | 0:09:14 | |
And some of the disasters of the early 20th century was trying to make the concert hall too big. | 0:09:14 | 0:09:19 | |
Did it change again then, when we started electrifying instruments | 0:09:19 | 0:09:22 | |
and putting big amps and... | 0:09:22 | 0:09:23 | |
You should change your hall when you get electronic reproduction. | 0:09:23 | 0:09:26 | |
One thing that a big decent concert hall has, | 0:09:26 | 0:09:28 | |
it has lots of absorbance that you can bring out and deaden the space. | 0:09:28 | 0:09:31 | |
Cos when you've actually got big loud speakers, electronic music, | 0:09:31 | 0:09:34 | |
you don't want the...you want to deaden it as much as you want. | 0:09:34 | 0:09:36 | |
So you end up with a very dead space, | 0:09:36 | 0:09:38 | |
so you have to have verbal acoustics to deal with, | 0:09:38 | 0:09:41 | |
concert halls deal with classical music, | 0:09:41 | 0:09:43 | |
but also, with the electronic enhancement and the electronic reproduction. | 0:09:43 | 0:09:46 | |
OK, so central to our elevation of music in our culture | 0:09:46 | 0:09:49 | |
has been the discovery of our own ability to make different sounds, | 0:09:49 | 0:09:52 | |
sounds that complement each other and can express emotion. | 0:09:52 | 0:09:54 | |
Of course, we've come a long way from the bone flute we heard about | 0:09:54 | 0:09:57 | |
to the instrument that's defined the last 60 years of music - the iconic electric guitar | 0:09:57 | 0:10:01 | |
of Hendrix and Townshend and Richards. | 0:10:01 | 0:10:04 | |
Many great artists have smashed up their guitar, | 0:10:04 | 0:10:06 | |
but usually as a statement of rebellion. | 0:10:06 | 0:10:08 | |
Mark Miodownik is taking one apart right now, | 0:10:08 | 0:10:10 | |
but, this time, in the name of science. | 0:10:10 | 0:10:13 | |
The Telecaster, as played by Keith Richards. | 0:10:16 | 0:10:18 | |
The Les Paul, Jimmy Page, | 0:10:18 | 0:10:20 | |
the Stratocaster, Jimi Hendrix, | 0:10:20 | 0:10:23 | |
and let's not forget the Flying V, Nigel Tufnel from Spinal Tap. | 0:10:23 | 0:10:28 | |
These guitars have defined the sound of rock and roll | 0:10:29 | 0:10:32 | |
and turned their players into rock gods, | 0:10:32 | 0:10:35 | |
and that's all down to the unique way they've been engineered. | 0:10:35 | 0:10:39 | |
So, the first thing to realise about an electric guitar | 0:10:39 | 0:10:42 | |
is that electricity comes out, it doesn't go in. | 0:10:42 | 0:10:44 | |
So, with an acoustic guitar, when you ping one of these strings, | 0:10:44 | 0:10:47 | |
you're creating a sound wave. | 0:10:47 | 0:10:49 | |
That's what you hear, that's the note. | 0:10:49 | 0:10:51 | |
With an electric guitar, it's slightly different. | 0:10:51 | 0:10:53 | |
Although you hear the same kind of note, | 0:10:53 | 0:10:56 | |
you're also creating an electrical oscillation, | 0:10:56 | 0:10:59 | |
and that is the key to an electric guitar. | 0:10:59 | 0:11:02 | |
'By connecting the guitar to an oscilloscope, | 0:11:02 | 0:11:05 | |
'you can see the electricity that's produced.' | 0:11:05 | 0:11:07 | |
So, that is... | 0:11:09 | 0:11:10 | |
the electrical wave that we've created by pinging the string, | 0:11:10 | 0:11:13 | |
and if I ping another string, I get a different frequency. | 0:11:13 | 0:11:17 | |
Converting the sound wave into an electric wave | 0:11:17 | 0:11:19 | |
means it can be amplified, manipulated and distorted. | 0:11:19 | 0:11:24 | |
This flexibility turned the guitar into a revolutionary instrument. | 0:11:24 | 0:11:28 | |
So, where does this electricity come from? | 0:11:28 | 0:11:31 | |
It comes from this, the pickup. | 0:11:31 | 0:11:33 | |
The pickup is magnetic. | 0:11:33 | 0:11:35 | |
In the 1830s, the scientist Michael Faraday | 0:11:35 | 0:11:38 | |
worked out how to use magnets to generate electricity. | 0:11:38 | 0:11:41 | |
You just need a coil of wire and some wrist action. | 0:11:41 | 0:11:44 | |
I'm just going to push the magnet through the coil of wire, like this. | 0:11:44 | 0:11:48 | |
And doing that, I'm generating electricity. | 0:11:48 | 0:11:50 | |
And that electricity is going through this little bulb and lights it up. | 0:11:50 | 0:11:53 | |
There it is! | 0:11:53 | 0:11:55 | |
It was almost exactly 100 years | 0:11:56 | 0:11:58 | |
before Faraday's theories were applied to the guitar. | 0:11:58 | 0:12:02 | |
But the principles at work are exactly the same, | 0:12:02 | 0:12:05 | |
and to prove it, I'm taking this Fender Telecaster, | 0:12:05 | 0:12:08 | |
the first mass-produced electric guitar, to bits. | 0:12:08 | 0:12:11 | |
So, here it is. | 0:12:12 | 0:12:14 | |
Some magnets surrounded by a coil of wire. | 0:12:14 | 0:12:17 | |
This is what it looks like when you take away that stuff. | 0:12:17 | 0:12:21 | |
Now, when the pickup is in the electric guitar, | 0:12:21 | 0:12:23 | |
these steel strings vibrate above each one of these little magnets, | 0:12:23 | 0:12:29 | |
and that disturbs the magnetic field, creating an electrical current. | 0:12:29 | 0:12:33 | |
So, what this pickup is doing | 0:12:33 | 0:12:34 | |
is turning a mechanical vibration into an electrical wave, | 0:12:34 | 0:12:38 | |
and that electrical wave travels down these wires into the amp, | 0:12:38 | 0:12:42 | |
and that's the sound you hear. | 0:12:42 | 0:12:45 | |
ELECTRICAL BUZZING | 0:12:45 | 0:12:46 | |
Now, I'm going to try and simulate that for you, with this magnet. | 0:12:46 | 0:12:50 | |
SOFT ELECTRICAL BUZZING SOUND | 0:12:50 | 0:12:52 | |
This affects the pickup's magnetic field, | 0:12:52 | 0:12:54 | |
in the same way a vibrating steel string does. | 0:12:54 | 0:12:57 | |
It's a bit bass-y, but that's because I can't vibrate it very fast. | 0:12:59 | 0:13:02 | |
But it's a sound, nonetheless. | 0:13:02 | 0:13:05 | |
That's quite cool! | 0:13:05 | 0:13:07 | |
Because the vibration of a guitar string varies along its length, | 0:13:07 | 0:13:10 | |
by having multiple pickups, | 0:13:10 | 0:13:12 | |
you can generate a range of treble and bass sounds. | 0:13:12 | 0:13:15 | |
And the amount you hear is controlled by these dials. | 0:13:15 | 0:13:18 | |
But the electric signal generated by these pickups is tiny, | 0:13:20 | 0:13:24 | |
and so, before it can be converted back into sound, | 0:13:24 | 0:13:27 | |
it needs to be amplified. | 0:13:27 | 0:13:28 | |
The amp is the unsung hero of the electric guitar. | 0:13:28 | 0:13:32 | |
Without it, the electricity produced by the pickup | 0:13:32 | 0:13:35 | |
is just too small to power a speaker. | 0:13:35 | 0:13:37 | |
Some people would even go so far as to say | 0:13:39 | 0:13:41 | |
that the amp is more important to the sound than the guitar itself. | 0:13:41 | 0:13:45 | |
HE LAUGHS That's heavier than it looks! | 0:13:48 | 0:13:51 | |
There's quite a few bits of gear here. | 0:13:51 | 0:13:53 | |
These two here are capacitors, | 0:13:53 | 0:13:54 | |
and they hold a huge amount of electric charge. | 0:13:54 | 0:13:56 | |
I'm not going to take those apart, | 0:13:56 | 0:13:58 | |
because that's actually seriously dangerous. | 0:13:58 | 0:14:00 | |
But actually, this is what I want to take apart. | 0:14:00 | 0:14:02 | |
This is the beating heart of the amp, the valve. | 0:14:02 | 0:14:05 | |
Wait until you see these. | 0:14:07 | 0:14:08 | |
They are beautiful. | 0:14:08 | 0:14:10 | |
Vacuum tubes, thermionic electron tubes or, simply, valves, | 0:14:12 | 0:14:17 | |
have been responsible for radio, TV, computers | 0:14:17 | 0:14:21 | |
and, of course, rock and roll. | 0:14:21 | 0:14:25 | |
The valve takes the tiny electrical current from the electric guitar | 0:14:25 | 0:14:29 | |
and amplifies it into a much bigger current that can drive the speaker. | 0:14:29 | 0:14:32 | |
In fact, the whole field of electronics only really began | 0:14:35 | 0:14:38 | |
when valves like this were invented. | 0:14:38 | 0:14:40 | |
Although valves look complicated, how they work is relatively simple. | 0:14:41 | 0:14:45 | |
The amp gets its power from the mains, | 0:14:45 | 0:14:48 | |
and sends a large current to the valves. | 0:14:48 | 0:14:51 | |
The electricity goes for the cathode to the anode, but on the way, | 0:14:51 | 0:14:55 | |
it has to go through this grid, which is connected to the electric guitar. | 0:14:55 | 0:14:58 | |
Now, the tiny current from the pickup is what goes into that grid, | 0:14:58 | 0:15:03 | |
so it imprints the pattern of the music onto this much larger current, | 0:15:03 | 0:15:07 | |
and it's that that gives you the loud sound. | 0:15:07 | 0:15:09 | |
Although valves have now mostly been replaced by transistors, | 0:15:09 | 0:15:13 | |
they're still much-loved by musicians, | 0:15:13 | 0:15:16 | |
for the unique tone and distortion they bring to the electric guitar, | 0:15:16 | 0:15:20 | |
especially when you turn up the volume. | 0:15:20 | 0:15:23 | |
APPLAUSE | 0:15:23 | 0:15:26 | |
That's the kind of thing we'll get criticised for, | 0:15:30 | 0:15:32 | |
because of people crying over your destruction | 0:15:32 | 0:15:35 | |
of a perfectly good electric guitar. Did it go back together OK? | 0:15:35 | 0:15:37 | |
-It went back together again in the end, yeah. -It's fine. | 0:15:37 | 0:15:40 | |
They're too expensive to destroy. The BBC budget is not that big. | 0:15:40 | 0:15:43 | |
Well, it stretched to you smashing a valve with a hammer. | 0:15:43 | 0:15:46 | |
We didn't put that back together. | 0:15:46 | 0:15:48 | |
-Now, what the instrument is made of is very important? -It is. | 0:15:48 | 0:15:51 | |
I mean, for an electric guitar, it's less important, | 0:15:51 | 0:15:53 | |
because you pick up the vibration of the string, | 0:15:53 | 0:15:56 | |
and actually, where you change the note is through the amplifier, | 0:15:56 | 0:15:58 | |
how you distort it through the amplifier. | 0:15:58 | 0:16:00 | |
Whereas, with a violin, the amplifier is that box, | 0:16:00 | 0:16:03 | |
and so, with the violin, you have to perfect that box to get the right sound. | 0:16:03 | 0:16:07 | |
Give me an example of the weirdest thing | 0:16:07 | 0:16:09 | |
you've seen an instrument made out of. | 0:16:09 | 0:16:11 | |
Well, maybe a vegetable, which I used to do as a party trick. | 0:16:11 | 0:16:13 | |
I've made a clarinet out of a giant Japanese radish once. | 0:16:13 | 0:16:17 | |
LAUGHTER | 0:16:17 | 0:16:18 | |
What kind of parties do you go to that have giant Japanese radish lying around? | 0:16:18 | 0:16:22 | |
-Sushi parties, obviously! -Well, obviously, yes! | 0:16:22 | 0:16:25 | |
How was the sound of it? | 0:16:25 | 0:16:27 | |
Well, someone once described it as sounding like a mating camel, | 0:16:27 | 0:16:29 | |
so maybe not the best kind of sound... | 0:16:29 | 0:16:31 | |
Yeah, but is that because you can't play, as it turns out, the flute? | 0:16:31 | 0:16:34 | |
You're going to make an instrument for us this evening, am I right? | 0:16:34 | 0:16:37 | |
-I am. -Using what? -Well... | 0:16:37 | 0:16:39 | |
I've commissioned a machine to make it for us. | 0:16:39 | 0:16:41 | |
-Is it our old friend...? -Our favourite machine. | 0:16:41 | 0:16:44 | |
The 3-D printer. The always impressive 3-D printer. | 0:16:44 | 0:16:46 | |
-We'll have it by the end of the show? -Yes, should do. | 0:16:46 | 0:16:48 | |
Now, let me talk about another part of this, Alex, | 0:16:48 | 0:16:51 | |
about our ability to recognise music. | 0:16:51 | 0:16:53 | |
I mean, it is astonishing how well it's encoded in the brain, | 0:16:53 | 0:16:58 | |
pieces of music, how quickly we recognise music. | 0:16:58 | 0:17:01 | |
Yeah, the music that we know... | 0:17:01 | 0:17:03 | |
We can pick up on very, very short segments and recognise, | 0:17:03 | 0:17:06 | |
"That's that track, that piece, that particular thing..." | 0:17:06 | 0:17:08 | |
And do we do this better with music than we do with say, | 0:17:08 | 0:17:11 | |
recognising the first line of a novel? | 0:17:11 | 0:17:13 | |
Are we more efficient with the information with music? | 0:17:13 | 0:17:15 | |
I think we get more information with music. | 0:17:15 | 0:17:17 | |
I mean, the first sentence of a novel | 0:17:17 | 0:17:19 | |
doesn't tell you where it's going. | 0:17:19 | 0:17:21 | |
We're very good at going, "Oh, yeah, that's..." | 0:17:21 | 0:17:23 | |
You know that rush when everybody gets on the dance floor cos they've heard... | 0:17:23 | 0:17:26 | |
It doesn't take long to happen. | 0:17:26 | 0:17:28 | |
We can demonstrate this with an exciting new game, | 0:17:28 | 0:17:30 | |
which has never featured on television before, | 0:17:30 | 0:17:32 | |
where we play a series of very short intros to well-known tunes, | 0:17:32 | 0:17:35 | |
and see if our guests or, indeed, the audience, can name them. | 0:17:35 | 0:17:39 | |
I call this, "Name That Piece Of Music," | 0:17:39 | 0:17:41 | |
but we're going to work on the title. | 0:17:41 | 0:17:44 | |
So, for example, let's have the first piece of music. | 0:17:44 | 0:17:47 | |
TWO SHORT BEATS PLAY | 0:17:47 | 0:17:49 | |
GROANING AND LAUGHTER | 0:17:49 | 0:17:51 | |
I think this really could work as a telly format. | 0:17:53 | 0:17:56 | |
LAUGHTER | 0:17:56 | 0:17:57 | |
I'm really excited by this. Go on, you on the couch. | 0:17:57 | 0:18:00 | |
I don't want to admit to knowing it, that's the thing... | 0:18:00 | 0:18:02 | |
-GROANING -The artist in question is beyond reproach, all right? It's fine. | 0:18:02 | 0:18:07 | |
-Who is it? -It was Lady Gaga, wasn't it? -No! | 0:18:07 | 0:18:10 | |
-It's Kylie! -GROANING AND LAUGHTER | 0:18:10 | 0:18:13 | |
-Oh, shame on you! -It's Kylie! -It's Kylie! -Oh, Kylie! | 0:18:13 | 0:18:16 | |
What's the name of the track? | 0:18:16 | 0:18:18 | |
-That's difficult, actually. -Yes! That's the thing. | 0:18:18 | 0:18:20 | |
I find I can't name tracks, there's too many. | 0:18:20 | 0:18:22 | |
Some people are better at this than others. | 0:18:22 | 0:18:25 | |
Yes, one that goes, "Na-na-na, na-na-na-na-na... | 0:18:25 | 0:18:27 | |
"Can't get you out of my head!" | 0:18:27 | 0:18:29 | |
Obviously, when we do this show properly, as a real format, | 0:18:29 | 0:18:32 | |
they'll tell the host what the names of the tunes are. | 0:18:32 | 0:18:35 | |
It works less well as a format if I am also trying to guess the tunes. | 0:18:35 | 0:18:39 | |
LAUGHTER | 0:18:39 | 0:18:41 | |
Fantastic! Let's try another one. | 0:18:41 | 0:18:43 | |
TWO BEATS PLAY | 0:18:43 | 0:18:44 | |
You can redeem yourself. | 0:18:44 | 0:18:47 | |
LAUGHTER | 0:18:47 | 0:18:49 | |
I can get it in my head, I can't think what the... | 0:18:49 | 0:18:51 | |
Do you know, I know that I don't know it. | 0:18:51 | 0:18:53 | |
-Oh, for Go...! We... -LAUGHTER AND APPLAUSE | 0:18:53 | 0:18:56 | |
This is fantastic. This whole thing was to justify YOUR theory. | 0:18:56 | 0:19:00 | |
"Oh, yeah, it's amazing. The human brain, given the slightest..." | 0:19:00 | 0:19:05 | |
It's James Brown! It could be... | 0:19:05 | 0:19:07 | |
TWO BEATS PLAY | 0:19:07 | 0:19:09 | |
Oh, I need a bit more. | 0:19:11 | 0:19:12 | |
BEATS PLAY AGAIN | 0:19:12 | 0:19:13 | |
-That's Bowie, isn't it? -Yes. Heroes. | 0:19:13 | 0:19:17 | |
Heroes... | 0:19:17 | 0:19:18 | |
-Yes, it is! -Did I get it right? -You got one right! | 0:19:18 | 0:19:21 | |
CHEERING AND APPLAUSE | 0:19:21 | 0:19:24 | |
Yes, we are very highly attuned to musical nuance, | 0:19:29 | 0:19:31 | |
and one of the things that is intrinsic to music is its rhythm. | 0:19:31 | 0:19:34 | |
Now, research into rhythm is turning up some extraordinary results. | 0:19:34 | 0:19:37 | |
Dr Tali Sharot went to the US to investigate. | 0:19:37 | 0:19:41 | |
DRUM BEAT PLAYS | 0:19:41 | 0:19:43 | |
Whenever you hear a beat, no matter how complex it is, | 0:19:47 | 0:19:50 | |
it probably makes you move. | 0:19:50 | 0:19:51 | |
Whether it's nodding your head or tapping your feet | 0:19:51 | 0:19:54 | |
or clicking your fingers, | 0:19:54 | 0:19:55 | |
you probably find it hard to resist. | 0:19:55 | 0:19:57 | |
'That's because our brains are wired for rhythm, | 0:19:57 | 0:20:00 | |
'so much so that rhythm has surprising therapeutic powers.' | 0:20:00 | 0:20:03 | |
'Rande Davis Gedalia was diagnosed with Parkinson's Disease in 2003.' | 0:20:07 | 0:20:11 | |
-Good to meet you. -Nice to meet you. | 0:20:12 | 0:20:14 | |
'She had serious problems with her movement | 0:20:14 | 0:20:17 | |
'until she joined a pioneering New York music therapy programme. | 0:20:17 | 0:20:20 | |
'And it changed her life.' | 0:20:20 | 0:20:22 | |
It was hard to balance | 0:20:22 | 0:20:25 | |
and the music kept me on beat. | 0:20:25 | 0:20:28 | |
I walk to the beat. Before, I had no beat. | 0:20:28 | 0:20:31 | |
Now, it gives me a sense of rhythm, a sense of order, | 0:20:31 | 0:20:35 | |
so my movement is way better. It's way better. I love it. | 0:20:35 | 0:20:39 | |
Rande learnt to use music | 0:20:39 | 0:20:42 | |
from doctors here at the Beth Israel Hospital in the Bronx, | 0:20:42 | 0:20:46 | |
where they've been treating patients with music for more than 30 years. | 0:20:46 | 0:20:51 | |
Concetta Tomaino is one of their most experienced doctors. | 0:20:51 | 0:20:54 | |
Parkinson's can lead to a variety of movement problems, | 0:20:56 | 0:21:00 | |
from getting the shakes to completely freezing up. | 0:21:00 | 0:21:02 | |
This happens because Parkinson's patients | 0:21:02 | 0:21:05 | |
have lost a large number of nerve cells | 0:21:05 | 0:21:07 | |
that produce a neurotransmitter, dopamine, | 0:21:07 | 0:21:09 | |
and dopamine is critical for co-ordinating our movement. | 0:21:09 | 0:21:13 | |
LOW, BASIC DRUM BEAT | 0:21:13 | 0:21:15 | |
Strong rhythms help her patients move more fluidly | 0:21:15 | 0:21:18 | |
and, together, they work out a playlist | 0:21:18 | 0:21:21 | |
they can use in their daily lives. | 0:21:21 | 0:21:23 | |
Rhythm works incredibly well. | 0:21:23 | 0:21:25 | |
People with Parkinson's sometimes perceive rhythm differently, | 0:21:25 | 0:21:28 | |
so you really have to work with each individual | 0:21:28 | 0:21:30 | |
to find out what pulse or what tempo is going to work best for them. | 0:21:30 | 0:21:34 | |
It drives motor function almost immediately | 0:21:34 | 0:21:36 | |
and I've seen this time and time again. | 0:21:36 | 0:21:39 | |
When rhythm therapy works, the effects are immediate, | 0:21:40 | 0:21:44 | |
and that tells us something rather astonishing about our brains. | 0:21:44 | 0:21:48 | |
Jessica Grahn is a cognitive neuroscientist | 0:21:49 | 0:21:52 | |
who studies music and the brain. | 0:21:52 | 0:21:55 | |
She's arranged to put one of her students in a brain scanner | 0:21:55 | 0:21:57 | |
while she listens to music, | 0:21:57 | 0:21:59 | |
to show me what's going on inside our brains when we hear rhythm. | 0:21:59 | 0:22:04 | |
OK, Ruth, now we're going to move onto the rhythms... | 0:22:04 | 0:22:07 | |
The results are striking. | 0:22:07 | 0:22:09 | |
The auditory cortex is active, as you'd expect, | 0:22:09 | 0:22:12 | |
but so are the motor regions of the brain. | 0:22:12 | 0:22:15 | |
All of these areas are areas that tend to respond to the control or initiation of movement | 0:22:15 | 0:22:22 | |
and these are very responsive in her brain, | 0:22:22 | 0:22:25 | |
even though she's staying perfectly still. | 0:22:25 | 0:22:27 | |
That's quite amazing, | 0:22:27 | 0:22:28 | |
because we see very robust activity in all of these motor regions | 0:22:28 | 0:22:32 | |
when people are not moving at all, | 0:22:32 | 0:22:34 | |
and not consciously thinking about movement, | 0:22:34 | 0:22:36 | |
just listening to music. | 0:22:36 | 0:22:38 | |
Yeah, we were really surprised the first time we saw it, too. | 0:22:38 | 0:22:41 | |
So, what did these responses tell us about Parkinson's patients | 0:22:41 | 0:22:45 | |
and why music therapy is so helpful for their movement? | 0:22:45 | 0:22:49 | |
What we think might be going on with listening to music and rhythm | 0:22:49 | 0:22:53 | |
is that this can bypass the faulty part of the circuit | 0:22:53 | 0:22:56 | |
and allow Parkinson's patients to then stand up and move. | 0:22:56 | 0:22:59 | |
So the music goes straight into the motor cortex? | 0:22:59 | 0:23:03 | |
It looks like it, yeah. | 0:23:03 | 0:23:04 | |
It seems our auditory and motor cortex are so deeply connected | 0:23:06 | 0:23:10 | |
that rhythm alone really does get us moving. | 0:23:10 | 0:23:12 | |
But rhythm therapy wouldn't work at all | 0:23:15 | 0:23:17 | |
without a very special skill called beat induction. | 0:23:17 | 0:23:21 | |
It's the ability, once we've heard a rhythm, to predict the next beat. | 0:23:22 | 0:23:27 | |
Laurel Trainor is trying to find out if it's something we're born with or something we learn, | 0:23:27 | 0:23:32 | |
by measuring the brain waves of babies | 0:23:32 | 0:23:34 | |
while they listen to simple rhythms. | 0:23:34 | 0:23:37 | |
SLOW BEEPING | 0:23:37 | 0:23:39 | |
Early results suggest that babies have this ability, | 0:23:39 | 0:23:42 | |
which means it may be something we are born with. | 0:23:42 | 0:23:45 | |
So, the red colour here shows there's activity just before the beat? | 0:23:47 | 0:23:51 | |
-That's right. -So, that shows us that they're predicting the beat... | 0:23:51 | 0:23:55 | |
Yes, absolutely. | 0:23:55 | 0:23:57 | |
Extraordinarily, beat induction seems to be unique to humans. | 0:23:57 | 0:24:02 | |
It hasn't been seen in any other primate. | 0:24:02 | 0:24:05 | |
So, what is the function of perceiving the beat, | 0:24:05 | 0:24:08 | |
and anticipating it, in humans? | 0:24:08 | 0:24:11 | |
There are probably two main reasons why we have it. | 0:24:11 | 0:24:14 | |
One is that when you can anticipate a beat, | 0:24:14 | 0:24:17 | |
you can dance with another person, you can move with another person. | 0:24:17 | 0:24:20 | |
When people move together, they bond socially. | 0:24:20 | 0:24:24 | |
A second reason why it's important | 0:24:24 | 0:24:26 | |
is because it's a necessary condition | 0:24:26 | 0:24:28 | |
for the evolution of language. | 0:24:28 | 0:24:30 | |
We have to hear the rhythm of the language, | 0:24:30 | 0:24:32 | |
but we also have to produce the rhythm of the language as we talk, | 0:24:32 | 0:24:36 | |
so we need this interaction between the auditory system and the motor system in order to do that. | 0:24:36 | 0:24:41 | |
As a neuroscientist, | 0:24:43 | 0:24:44 | |
I was really surprised by how close the connection is | 0:24:44 | 0:24:48 | |
between the sound system and our motor system, | 0:24:48 | 0:24:50 | |
but now that I think about it, it's all around us. | 0:24:50 | 0:24:53 | |
It's in my step when I walk, it's when I speak, | 0:24:53 | 0:24:56 | |
and it may just be fundamental to what makes us human. | 0:24:56 | 0:25:00 | |
APPLAUSE | 0:25:02 | 0:25:05 | |
In some ways, the results of that are astonishing, | 0:25:09 | 0:25:12 | |
and in other ways, they seem like the most obvious thing in the world. | 0:25:12 | 0:25:14 | |
We all listen to music as we walk along. | 0:25:14 | 0:25:16 | |
Since the Walkman, our generation has soundtracked ourselves, | 0:25:16 | 0:25:19 | |
knowing that it can increase the step... | 0:25:19 | 0:25:21 | |
But it literally is bypassing a damaged area of the brain? | 0:25:21 | 0:25:25 | |
Yeah, what's really interesting there | 0:25:25 | 0:25:27 | |
is that if you have one structure that's damaged, | 0:25:27 | 0:25:30 | |
or one pathway that's damaged, | 0:25:30 | 0:25:32 | |
and you lose a function, whether it's movement or language, | 0:25:32 | 0:25:36 | |
there might be a way to bypass it, by using a different trigger. | 0:25:36 | 0:25:39 | |
Alex, were you impressed by this kind of work? | 0:25:39 | 0:25:42 | |
Yeah, I think it's tapping into what we know | 0:25:42 | 0:25:44 | |
about the idea of synchronisation being really important in music | 0:25:44 | 0:25:47 | |
and somehow providing that in a different way. | 0:25:47 | 0:25:49 | |
And I like the approach of saying, | 0:25:49 | 0:25:51 | |
"OK, we have a limitation with Parkinson's. | 0:25:51 | 0:25:53 | |
"Let's try and find another way round." | 0:25:53 | 0:25:55 | |
So, yeah, finding something that is also intrinsically enjoyable, | 0:25:55 | 0:25:59 | |
and I think the idea of getting through pain | 0:25:59 | 0:26:01 | |
and getting through difficult situations with music | 0:26:01 | 0:26:03 | |
is one of the reasons why it's so useful for us. | 0:26:03 | 0:26:05 | |
Is this a uniquely human thing? | 0:26:05 | 0:26:07 | |
Interestingly, monkeys don't have the same musical abilities that we do, | 0:26:07 | 0:26:11 | |
which is interesting, because they are our closest genetic relatives. | 0:26:11 | 0:26:15 | |
But they can't do it. | 0:26:15 | 0:26:16 | |
They can't distinguish between different types of music. | 0:26:16 | 0:26:19 | |
They don't have music preference, like we do. | 0:26:19 | 0:26:21 | |
-They actually prefer silence to music. -Really? | 0:26:21 | 0:26:24 | |
Yeah. Tamarins, particularly, have been shown to prefer... | 0:26:24 | 0:26:27 | |
If they're in a situation where they can choose where they go, | 0:26:27 | 0:26:29 | |
if there's some music playing and some place where there isn't music, | 0:26:29 | 0:26:32 | |
-they always go to the place without music. -Lovely. | 0:26:32 | 0:26:35 | |
Now, I know we're bombarding you with lots of information, | 0:26:35 | 0:26:37 | |
but you can always get involved by following us @bbcscienceclub, | 0:26:37 | 0:26:41 | |
or by visiting our website... | 0:26:41 | 0:26:42 | |
APPLAUSE | 0:26:49 | 0:26:52 | |
So, we've seen some of the effect that music has on the brain, | 0:26:53 | 0:26:57 | |
but it's a physical process. | 0:26:57 | 0:26:59 | |
It's just a change in air pressure around us | 0:26:59 | 0:27:01 | |
that we hear arriving in waves. | 0:27:01 | 0:27:02 | |
And like any waves, there's a spectrum of frequencies. | 0:27:02 | 0:27:05 | |
Not that we can hear them all. | 0:27:05 | 0:27:06 | |
We can only hear a particular range, am I right? | 0:27:06 | 0:27:09 | |
-Exactly, yes. -Do you know what the uppers and lowers of these are? | 0:27:09 | 0:27:12 | |
Well, it depends on your age. | 0:27:12 | 0:27:13 | |
-You lose certain frequencies as you get older? -Yeah. | 0:27:13 | 0:27:16 | |
Basically, when you're 20, your hearing is as good as it ever gets, | 0:27:16 | 0:27:19 | |
and it's downhill from there, and you gradually lose high frequencies. | 0:27:19 | 0:27:22 | |
You don't notice that, probably, until you get into middle age, | 0:27:22 | 0:27:25 | |
when it starts just edging towards speech frequencies... | 0:27:25 | 0:27:28 | |
So, the higher frequencies are the ones that go first? | 0:27:28 | 0:27:30 | |
Let's get a sample of what we're talking about. | 0:27:30 | 0:27:32 | |
This is an app, by the way, that's been driving all this stuff. | 0:27:32 | 0:27:35 | |
LOW ELECTRONIC BEEP So, this is a note. Can everyone hear that? | 0:27:35 | 0:27:39 | |
-How many hertz is that? -That's 1,000 hertz. -OK. | 0:27:39 | 0:27:43 | |
Basically, if you can't hear this, there's a really big problem. | 0:27:43 | 0:27:46 | |
We're going to test you. That's 1,000 hertz. | 0:27:46 | 0:27:48 | |
All hands up if you can hear that. Now, that should be... | 0:27:48 | 0:27:51 | |
That's pretty much everyone here, including ourselves. | 0:27:51 | 0:27:54 | |
No, no, leave them up. Leave them up, please. | 0:27:54 | 0:27:57 | |
Right, 5,000. | 0:27:57 | 0:27:58 | |
HIGH-PITCHED BEEPING | 0:27:58 | 0:28:00 | |
-Everyone hear it? Fantastic. 10,000? -Young crowd... | 0:28:00 | 0:28:04 | |
Right, who can hear that? | 0:28:04 | 0:28:06 | |
We haven't lost any hands at all. 13... | 0:28:06 | 0:28:08 | |
-I can't hear anything. -Can't hear a thing. | 0:28:10 | 0:28:12 | |
Can the rest of you all hear that? | 0:28:12 | 0:28:15 | |
-That's amazing. -It's really weird! | 0:28:15 | 0:28:17 | |
It's really strange. Right, let's try 15... | 0:28:17 | 0:28:19 | |
It's going to turn into a weird auction. | 0:28:19 | 0:28:21 | |
The winner is the person with the best ears. | 0:28:21 | 0:28:24 | |
Wow! Really?! | 0:28:24 | 0:28:26 | |
-Are you just doing this? Is it part of a gag? -LAUGHTER | 0:28:26 | 0:28:29 | |
-OK, what are you up to now? -This is 17,000. | 0:28:29 | 0:28:32 | |
Oh, we lost a few people at 17,000. | 0:28:33 | 0:28:35 | |
OK. No, we lost most people at 17,000. | 0:28:35 | 0:28:37 | |
You're still hearing it? Really faint? OK. | 0:28:37 | 0:28:40 | |
-Are you bluffing? -Let's try 18... | 0:28:40 | 0:28:42 | |
-Is that everyone? -There's one there in the front. Look! | 0:28:45 | 0:28:48 | |
Oh, you as well. You're still in. | 0:28:48 | 0:28:50 | |
Gone. We lost you somewhere between 18,000. | 0:28:52 | 0:28:53 | |
Well done you, though. Give her a round of applause, that's fantastic. | 0:28:53 | 0:28:57 | |
APPLAUSE | 0:28:57 | 0:28:59 | |
This phenomenon became very well-known, by the way, | 0:28:59 | 0:29:01 | |
because some company marketed an alarm | 0:29:01 | 0:29:04 | |
that shopkeepers could play outside their shops | 0:29:04 | 0:29:07 | |
to clear teenagers from in front of the shop, | 0:29:07 | 0:29:10 | |
because only teenagers could hear it. | 0:29:10 | 0:29:12 | |
My favourite thing about it is that the teenagers recorded the tone | 0:29:12 | 0:29:15 | |
and used it as a ringtone on their phone, | 0:29:15 | 0:29:17 | |
because teachers can't hear it in school. | 0:29:17 | 0:29:19 | |
So, they can actually phone each other in class, | 0:29:19 | 0:29:21 | |
which I think is genius. | 0:29:21 | 0:29:23 | |
So, that's the frequency. What are the physical effects? | 0:29:23 | 0:29:26 | |
I can show you a particularly nice example here, | 0:29:26 | 0:29:29 | |
where you can actually... | 0:29:29 | 0:29:30 | |
If we can find the resonant frequency of a wine glass... GLASS TINKLES | 0:29:30 | 0:29:34 | |
So, that's its resonant frequency. | 0:29:34 | 0:29:35 | |
That note is what you'd want to achieve, yeah? | 0:29:35 | 0:29:37 | |
If you then force it to vibrate at that frequency, | 0:29:37 | 0:29:40 | |
then it will vibrate so violently that it will break. | 0:29:40 | 0:29:42 | |
Fabulous. Great. I'm into that in a huge way. | 0:29:42 | 0:29:44 | |
In theory! I meant to say, in theory. | 0:29:44 | 0:29:46 | |
Yeah, no, let's just keep doing it until we get it to break. | 0:29:46 | 0:29:50 | |
Everyone ready? Do you have your fingers in your ears or something on? | 0:29:50 | 0:29:53 | |
By the way, this trick used to be done by opera singers, didn't it? | 0:29:53 | 0:29:57 | |
It's actually really difficult to do. To do it, you have to... | 0:29:57 | 0:30:00 | |
If I just nick it for a second... | 0:30:00 | 0:30:02 | |
You have to get it that close to your mouth. | 0:30:02 | 0:30:04 | |
As we shall see in a moment, when the glass goes... | 0:30:04 | 0:30:06 | |
glass in your mouth is a really stupid thing to do. | 0:30:06 | 0:30:08 | |
So, we know we're at the right frequency | 0:30:08 | 0:30:10 | |
if we get the piece of paper to vibrate? | 0:30:10 | 0:30:12 | |
Yeah, so that's going to vibrate the glass, | 0:30:12 | 0:30:14 | |
which will make the paper jump. | 0:30:14 | 0:30:16 | |
So, the minute the paper jumps, you just crank up the volume? | 0:30:16 | 0:30:19 | |
Right. OK, are you ready? | 0:30:19 | 0:30:20 | |
PITCH OF NOTE INCREASES | 0:30:20 | 0:30:23 | |
-How exact do you have to be here? -Very exact. | 0:30:23 | 0:30:27 | |
-Can you see that going? -I can, yeah. That is spooky. | 0:30:27 | 0:30:30 | |
HIGH-PITCHED BEEPING | 0:30:30 | 0:30:33 | |
It's quite loud. | 0:30:33 | 0:30:34 | |
I can even see it vibrating. | 0:30:37 | 0:30:38 | |
Oh! Oh, oh, oh! | 0:30:44 | 0:30:47 | |
LAUGHTER | 0:30:47 | 0:30:49 | |
APPLAUSE | 0:30:49 | 0:30:52 | |
Wow! | 0:30:52 | 0:30:54 | |
I'm loving the tension of the build-up. | 0:30:56 | 0:30:58 | |
You took a long enough to get there, didn't you? We have... | 0:30:58 | 0:31:01 | |
You did wrong with a proper high-speed camera. | 0:31:01 | 0:31:03 | |
So, our institute did one a few years ago with a slow-motion camera. | 0:31:03 | 0:31:07 | |
-This is it. -Wow, it wobbles quite significantly. | 0:31:07 | 0:31:10 | |
Bottom bit goes first. How is the top bit holding together? | 0:31:10 | 0:31:14 | |
Yeah, that's incredible. That shows you just how fast the frame rate is. | 0:31:14 | 0:31:17 | |
-Imagine if that was near your mouth and was tumbling that way. -Yeah. | 0:31:19 | 0:31:24 | |
-So, not recommended. -No, but cool! | 0:31:24 | 0:31:26 | |
Hey, if any of your glassware smashed during that...tweet us. | 0:31:27 | 0:31:31 | |
LAUGHTER | 0:31:31 | 0:31:33 | |
As you're just brushing them around... No, hopefully it didn't. | 0:31:33 | 0:31:36 | |
I've always wanted to do that. Thank you very much, Mark. | 0:31:36 | 0:31:39 | |
APPLAUSE | 0:31:39 | 0:31:42 | |
Still to come on tonight's show, | 0:31:43 | 0:31:45 | |
Alok Jha investigates whether computers are killing music. | 0:31:45 | 0:31:49 | |
But first, the most remarkable thing about music | 0:31:49 | 0:31:51 | |
is how these wave forms and frequencies | 0:31:51 | 0:31:53 | |
are translated into tangible emotional effects by our brains. | 0:31:53 | 0:31:56 | |
To find out how a piece of music moves us, | 0:31:56 | 0:31:58 | |
we sent James May to have his head examined. | 0:31:58 | 0:32:01 | |
MUSIC: "Toccata and Fugue in D Minor" by Bach | 0:32:01 | 0:32:04 | |
Many years ago, I did a music degree | 0:32:04 | 0:32:07 | |
and I came away convinced of one thing, | 0:32:07 | 0:32:10 | |
that music has a real emotional grip on us that's hard to explain, | 0:32:10 | 0:32:15 | |
and I've always wanted to know why. | 0:32:15 | 0:32:17 | |
Why is it that a simple chord change in a pop song | 0:32:18 | 0:32:21 | |
can have the capacity almost to burst your heart? | 0:32:21 | 0:32:24 | |
Why is it that a single, supposedly wrong, note in Chopin | 0:32:24 | 0:32:29 | |
can turn mere organised sound | 0:32:29 | 0:32:31 | |
into something that seems to scratch at the very kernel | 0:32:31 | 0:32:35 | |
of human self awareness? | 0:32:35 | 0:32:37 | |
So, to see if science has an explanation, I've come to Berlin. | 0:32:37 | 0:32:40 | |
My first stop is the Technical University, | 0:32:42 | 0:32:44 | |
where Hauke Egermann is a music psychologist. | 0:32:44 | 0:32:47 | |
I haven't been allowed to bring any of my own music to this experiment. | 0:32:49 | 0:32:53 | |
Nothing that I love, nothing that I'm familiar with. | 0:32:53 | 0:32:55 | |
I have to listen to something I've never heard before, | 0:32:55 | 0:32:58 | |
and then we will measure my reaction to it. | 0:32:58 | 0:33:01 | |
Right, you want to attach electrodes to me? | 0:33:01 | 0:33:03 | |
Yes, please. Have a seat. | 0:33:03 | 0:33:04 | |
These clips and electrodes are going to monitor | 0:33:04 | 0:33:08 | |
changes in my skin's electrical conductivity. | 0:33:08 | 0:33:11 | |
Apparently, it's a scientific measure of involuntary emotional arousal. | 0:33:11 | 0:33:17 | |
So, when it starts playing, I want you to press the left mouse button | 0:33:17 | 0:33:20 | |
-and then continuously rate how the music makes you feel, OK? -OK. | 0:33:20 | 0:33:24 | |
CLASSICAL PIECE BEGINS TO PLAY | 0:33:24 | 0:33:28 | |
This is composed by a Frenchman called Edgar Varese. | 0:33:28 | 0:33:31 | |
It's a bit strange, but I rather like it... | 0:33:34 | 0:33:36 | |
Is that the end? | 0:33:45 | 0:33:47 | |
-That's the end, yes. -How did I do? | 0:33:47 | 0:33:49 | |
HAUKE LAUGHS | 0:33:49 | 0:33:50 | |
-Well, we'll see. -Am I dead? -You did fine. | 0:33:50 | 0:33:53 | |
We can see that there are actually some moments here | 0:33:53 | 0:33:57 | |
where, especially, your skin conductance response | 0:33:57 | 0:34:01 | |
is really reacting to individual events in the music. | 0:34:01 | 0:34:05 | |
This could be that something surprised you, | 0:34:05 | 0:34:10 | |
or you had an intense emotion linked to certain events in the music. | 0:34:10 | 0:34:14 | |
It seems all of us respond in roughly the same way | 0:34:14 | 0:34:17 | |
to acoustic changes in music. | 0:34:17 | 0:34:20 | |
But that doesn't explain why we respond emotionally. | 0:34:20 | 0:34:23 | |
When I put this to Hauke, he played me this... | 0:34:23 | 0:34:26 | |
MUSIC: "Symphony No.4 in A Major" by Mendelssohn | 0:34:26 | 0:34:30 | |
..and then these voices. | 0:34:33 | 0:34:35 | |
'I won the lottery, and I still can't believe it!' | 0:34:35 | 0:34:38 | |
'I've finally bought the car I've always dreamed about.' | 0:34:38 | 0:34:41 | |
That "da-deh-deh...", which I tend to think of as being | 0:34:41 | 0:34:45 | |
a sort of hunting, horse-riding motif in music | 0:34:45 | 0:34:48 | |
is also, actually, now you point it out, very similar to that | 0:34:48 | 0:34:51 | |
AMERICAN ACCENT: "Oh, my Gaaad!" | 0:34:51 | 0:34:53 | |
What you're sort of saying is, | 0:34:53 | 0:34:55 | |
major keys sound like people speaking positively and excitedly. | 0:34:55 | 0:34:59 | |
-That's the point. -So, have you got a clip in a minor key | 0:34:59 | 0:35:01 | |
and then someone saying they've lost their lottery ticket? | 0:35:01 | 0:35:04 | |
Yes. | 0:35:04 | 0:35:06 | |
'It only took a moment for the accident to happen. | 0:35:06 | 0:35:08 | |
'We were laughing and joking about things | 0:35:08 | 0:35:11 | |
'when the truck crossed the median and hit us.' | 0:35:11 | 0:35:13 | |
Now, this gets very interesting now. | 0:35:13 | 0:35:15 | |
Had that been a German woman talking in German, | 0:35:15 | 0:35:18 | |
I would have still known she was talking about something sad. | 0:35:18 | 0:35:21 | |
The idea is that these expressive features, | 0:35:21 | 0:35:24 | |
they're supposed to work in different cultures | 0:35:24 | 0:35:26 | |
everywhere in the world. | 0:35:26 | 0:35:27 | |
But all of that was with music I didn't know. | 0:35:27 | 0:35:30 | |
Now, we're going to see how I react to music I know and love. | 0:35:30 | 0:35:34 | |
All right, James, let me lead you through our scanner room. | 0:35:36 | 0:35:40 | |
I'm going to have my brain scanned by music psychologist Stefan Koelsch. | 0:35:40 | 0:35:45 | |
Close your eyes, please... | 0:35:45 | 0:35:46 | |
To see just how deep my love of music really is, | 0:35:46 | 0:35:49 | |
I'm going to listen to my absolute favourite piece of Bach, | 0:35:49 | 0:35:52 | |
his toccata in G minor. | 0:35:52 | 0:35:54 | |
MUSIC: "Toccata in G Minor" by Bach | 0:35:54 | 0:35:56 | |
Are you feeling OK in there? | 0:36:03 | 0:36:05 | |
-'Yes, I am. Very relaxed.' -Oh, right. | 0:36:05 | 0:36:07 | |
And for comparison, | 0:36:07 | 0:36:09 | |
music that I have absolutely no emotional attachment to... | 0:36:09 | 0:36:13 | |
Jedward's Lipstick. | 0:36:13 | 0:36:14 | |
# You say you're on it, but you just don't know | 0:36:20 | 0:36:23 | |
# You're spending money like you're on Death Row... # | 0:36:23 | 0:36:26 | |
HE LAUGHS Thank you for the Jedward. | 0:36:26 | 0:36:28 | |
'Time to find out what happened.' | 0:36:28 | 0:36:30 | |
So, my brain is present? | 0:36:30 | 0:36:32 | |
-Oh, yeah. -That's reassuring. | 0:36:32 | 0:36:34 | |
Wow, look at this. Wow, beautiful. | 0:36:34 | 0:36:36 | |
-Thank you. -This experiment apparently really worked. | 0:36:36 | 0:36:39 | |
Stefan's team have laid both my listening experiences | 0:36:39 | 0:36:43 | |
on top of each other. | 0:36:43 | 0:36:44 | |
Red is my response to Bach, | 0:36:46 | 0:36:47 | |
and Jedward is represented | 0:36:47 | 0:36:49 | |
by the practically non-existent blue. | 0:36:49 | 0:36:51 | |
Yeah, it's a very clear result here. | 0:36:53 | 0:36:56 | |
So, I've got Krakatoa of Bach reaction there, | 0:36:56 | 0:36:59 | |
but only a sort of faltering cigarette lighter for Jedward. | 0:36:59 | 0:37:02 | |
Is that fair? | 0:37:02 | 0:37:04 | |
Yeah, that's correct and that shows us | 0:37:04 | 0:37:06 | |
that you had much more pleasurable experience to your preferred music | 0:37:06 | 0:37:10 | |
than to the unpreferred. | 0:37:10 | 0:37:12 | |
And it seems the pleasure gets me | 0:37:12 | 0:37:14 | |
right in the deepest, most primitive parts of my brain, | 0:37:14 | 0:37:17 | |
the amygdala, the hippocampus, | 0:37:17 | 0:37:20 | |
and a reward centre called the nucleus accumbens. | 0:37:20 | 0:37:23 | |
This is the structure where dopamine is released in the brain. | 0:37:23 | 0:37:28 | |
And dopamine does...? | 0:37:28 | 0:37:30 | |
It is released in situations where we feel great pleasure. | 0:37:30 | 0:37:35 | |
For example, if we drink a glass of water when we are thirsty, | 0:37:35 | 0:37:39 | |
when we are having sex, when we eat something when we are hungry... | 0:37:39 | 0:37:43 | |
So, if you could put two people having sex in the scanner... | 0:37:43 | 0:37:46 | |
I know there isn't space, | 0:37:46 | 0:37:47 | |
but you would get the same bits of their brains glowing | 0:37:47 | 0:37:51 | |
as you do when they listen to music? | 0:37:51 | 0:37:53 | |
Which means music is, scientifically speaking, orgasmic. | 0:37:53 | 0:37:57 | |
-Yeah... -And scientifically proved. Here it is. -It is, yes. | 0:37:57 | 0:38:00 | |
APPLAUSE | 0:38:03 | 0:38:05 | |
Ladies and gentlemen, James May. | 0:38:11 | 0:38:13 | |
APPLAUSE | 0:38:13 | 0:38:17 | |
So, James, it turns out that at a very fundamental, basic level, | 0:38:20 | 0:38:24 | |
almost at a primitive level, you're a musical snob. | 0:38:24 | 0:38:27 | |
-Yes. -What's your problem with Jedward? | 0:38:27 | 0:38:29 | |
Well, I don't have a particular problem with Jedward. | 0:38:29 | 0:38:32 | |
Well, I do, actually. It's the inevitability of the sort of... | 0:38:32 | 0:38:35 | |
HE IMITATES REPETITIVE BEAT | 0:38:35 | 0:38:37 | |
I know it will always go... HE IMITATES BEAT AGAIN | 0:38:37 | 0:38:39 | |
So, you can predict the rhythm, like a six-month-old child. | 0:38:39 | 0:38:42 | |
LAUGHTER | 0:38:42 | 0:38:45 | |
But it did prove something that I've always suspected, | 0:38:45 | 0:38:47 | |
which is that outside the sphere of regular musical appreciation, | 0:38:47 | 0:38:52 | |
which is sort of intellect, culture, experience, learning, all those things, | 0:38:52 | 0:38:56 | |
there's a sort of grey area where it appeals directly to the emotions, | 0:38:56 | 0:39:01 | |
this most widely documented | 0:39:01 | 0:39:03 | |
but, I think, least understood bit of the human existence. | 0:39:03 | 0:39:07 | |
And I found that very reassuring. | 0:39:07 | 0:39:10 | |
It does mean that the music that you get off on is a fundamental need, | 0:39:10 | 0:39:15 | |
along with eating, as you were saying, drinking, | 0:39:15 | 0:39:19 | |
orgasm, ejaculation... or a really good kebab. | 0:39:19 | 0:39:21 | |
LAUGHTER | 0:39:21 | 0:39:24 | |
This is the basic stuff of life, basically. | 0:39:24 | 0:39:26 | |
And one hell of a night, by the way! | 0:39:26 | 0:39:28 | |
LAUGHTER | 0:39:28 | 0:39:31 | |
But the order would have been slightly weird. | 0:39:31 | 0:39:34 | |
I mean, buy her dinner first, for God's sake(!) | 0:39:34 | 0:39:37 | |
It always ends with a kebab, Dara. | 0:39:37 | 0:39:39 | |
But, yes, it is, because it is very deep recesses of the brain. | 0:39:39 | 0:39:42 | |
This is very fundamental. | 0:39:42 | 0:39:44 | |
Some would say stuff that was there earliest in our evolution, | 0:39:44 | 0:39:47 | |
that music is appealing to. | 0:39:47 | 0:39:49 | |
Yes, which is probably why it's in every human culture | 0:39:49 | 0:39:51 | |
and why it's so important, because you can't explain it, | 0:39:51 | 0:39:54 | |
you can't express it terribly well. | 0:39:54 | 0:39:55 | |
And, like James says, | 0:39:55 | 0:39:57 | |
we're still really figuring out how this all works. | 0:39:57 | 0:39:59 | |
And we're more naturally likely to speak in a major key | 0:39:59 | 0:40:02 | |
when we're delivering happy news? | 0:40:02 | 0:40:04 | |
It depends what you're saying. | 0:40:04 | 0:40:06 | |
Speech is atonal, it doesn't fit into keys. That's a construct. | 0:40:06 | 0:40:10 | |
But, broadly speaking, you were in a major key there. | 0:40:10 | 0:40:13 | |
But we're simplifying it massively, | 0:40:13 | 0:40:15 | |
because music essentially in major key | 0:40:15 | 0:40:17 | |
will still move through minor keys as part of its musical dialogue, | 0:40:17 | 0:40:21 | |
as part of the sense that it makes, | 0:40:21 | 0:40:22 | |
and then you get contrasts and, you know, | 0:40:22 | 0:40:24 | |
"Oh, that was a pity, but, hey, never mind." | 0:40:24 | 0:40:26 | |
Of course, you're responsible for a great deal of "music as a motivational tool" | 0:40:26 | 0:40:31 | |
with the 18 and counting Top Gear Driving Music albums, | 0:40:31 | 0:40:35 | |
which have been released to date... | 0:40:35 | 0:40:37 | |
They were nothing to do with me, though. | 0:40:37 | 0:40:39 | |
But tracks like Don't Stop Me Now by Queen, I think, | 0:40:39 | 0:40:41 | |
was voted on some Top Gear website as the best... | 0:40:41 | 0:40:44 | |
Neurologically, what do you think you are achieving | 0:40:44 | 0:40:46 | |
with this body of work? | 0:40:46 | 0:40:47 | |
LAUGHTER | 0:40:47 | 0:40:49 | |
Umm...I don't know. | 0:40:49 | 0:40:51 | |
But driving music is an interesting idea, | 0:40:51 | 0:40:53 | |
because the rules are different in the car from the rest of life, | 0:40:53 | 0:40:57 | |
and that's bodily hygiene, opinions, music that you listen to, | 0:40:57 | 0:41:01 | |
all the rest of it. And it's... | 0:41:01 | 0:41:03 | |
..they're lower. | 0:41:05 | 0:41:06 | |
One thing is, you can't listen to, say, | 0:41:06 | 0:41:08 | |
Schubert's string quartet in the car, because most cars are too noisy. | 0:41:08 | 0:41:12 | |
The dynamic range of classical music is too great, | 0:41:12 | 0:41:14 | |
whereas pop music is reasonably level, for the most part. | 0:41:14 | 0:41:18 | |
Music with a regular beat, a regular form, | 0:41:18 | 0:41:21 | |
chorus, you know, refrain, middle eight, and all the rest of it, | 0:41:21 | 0:41:24 | |
suits the sort of slightly banal, but very involving, act of driving. | 0:41:24 | 0:41:29 | |
-Yes. -Does that make sense? -That makes perfect... | 0:41:29 | 0:41:31 | |
Put that on the liner notes on the sleeve of Top Gear 18. | 0:41:31 | 0:41:36 | |
You wouldn't put it like that. | 0:41:36 | 0:41:38 | |
You'd put, sort of, "25 gut-busting, tyre-smoking tracks." | 0:41:38 | 0:41:40 | |
LAUGHTER | 0:41:40 | 0:41:42 | |
That is kind of the shtick, all right. OK. | 0:41:42 | 0:41:45 | |
Do any of you own a top Gear album? | 0:41:45 | 0:41:47 | |
No. That's fine. The weird thing is... | 0:41:49 | 0:41:51 | |
Don't get all snooty. Don't you get all snooty! | 0:41:51 | 0:41:54 | |
Because you'll own the tracks, you'll definitely... | 0:41:54 | 0:41:57 | |
You'll own the most of those tracks in some shape or form, | 0:41:57 | 0:41:59 | |
because that's really the way it's evolved, because of technology. | 0:41:59 | 0:42:02 | |
Music was first recorded in 1877, | 0:42:02 | 0:42:05 | |
and the amount of music we have access to | 0:42:05 | 0:42:07 | |
has changed and grown dramatically, as you might have guessed. | 0:42:07 | 0:42:10 | |
Here's the data. | 0:42:10 | 0:42:11 | |
Technology has transformed the way we consume music. | 0:42:13 | 0:42:17 | |
In the 1980s, it's reckoned the average 16- to 24-year-old | 0:42:17 | 0:42:20 | |
had a record collection that consisted of 150 songs. | 0:42:20 | 0:42:25 | |
By 2009, that figure had grown to over 8,000 songs. | 0:42:25 | 0:42:30 | |
A vinyl LP plays for around 45 minutes and holds about 12 songs. | 0:42:30 | 0:42:35 | |
The C90 cassette tape holds 22 songs. | 0:42:35 | 0:42:38 | |
A CD plays 21 songs for about 80 minutes, | 0:42:38 | 0:42:42 | |
whereas a 160GB MP3 player can hold 40,000 songs, | 0:42:42 | 0:42:48 | |
that's 160,000 minutes, | 0:42:48 | 0:42:50 | |
almost 16 weeks of continuous play. | 0:42:50 | 0:42:54 | |
The MP3 player weighs 140 grammes. | 0:42:54 | 0:42:57 | |
If you were to carry around that amount of vinyl, | 0:42:57 | 0:42:59 | |
it would weigh 640kg, | 0:42:59 | 0:43:01 | |
which is the equivalent of carrying a large horse in your pocket. | 0:43:01 | 0:43:05 | |
APPLAUSE | 0:43:07 | 0:43:09 | |
Now, if we were to ask you who the most influential person was | 0:43:09 | 0:43:12 | |
in electronic music, you might have said Robert Moog, | 0:43:12 | 0:43:15 | |
for his synthesiser, or Brian Eno, or Kraftwerk, | 0:43:15 | 0:43:17 | |
or the Chemical Brothers, but none of these, really. | 0:43:17 | 0:43:20 | |
It's a woman called Daphne Oram, | 0:43:20 | 0:43:22 | |
who arrived at the BBC as a sound engineer in 1943, | 0:43:22 | 0:43:25 | |
and began to experiment with the effects that she could create | 0:43:25 | 0:43:28 | |
with the equipment there. | 0:43:28 | 0:43:29 | |
She then set up the first radiophonic workshop, | 0:43:29 | 0:43:32 | |
which basically initiated sound effects and electronic music, | 0:43:32 | 0:43:36 | |
and this was done almost as an after-hours hobby of hers. | 0:43:36 | 0:43:39 | |
In fact, she was regarded so strangely | 0:43:39 | 0:43:41 | |
that she actually appeared in a news story from 1962. | 0:43:41 | 0:43:44 | |
You should just see the scepticism of the reporter and, indeed, | 0:43:44 | 0:43:47 | |
the fantastically clipped Received Pronunciation. | 0:43:47 | 0:43:50 | |
Have a look at this. | 0:43:50 | 0:43:52 | |
ELECTRONIC BURBLING | 0:43:52 | 0:43:54 | |
Welcome to Tower Folly, | 0:43:56 | 0:43:58 | |
this lonely oast house on the North Downs of Kent. | 0:43:58 | 0:44:02 | |
Well, as far as I know, this house isn't haunted, | 0:44:02 | 0:44:04 | |
and there isn't a mad scientist in sight. | 0:44:04 | 0:44:07 | |
This is, in fact, a music factory, | 0:44:07 | 0:44:09 | |
where they can literally make music out of electronic sounds. | 0:44:09 | 0:44:13 | |
And the woman who makes it | 0:44:13 | 0:44:15 | |
has just been awarded a grant by the Gulbenkian Foundation | 0:44:15 | 0:44:18 | |
to help her research. | 0:44:18 | 0:44:20 | |
She's here at her control box, Miss Daphne Oram. | 0:44:20 | 0:44:23 | |
Now, Miss Oram, how did you get involved in this kind of work? | 0:44:23 | 0:44:26 | |
Well, it dates back, really, to 1944, I think, | 0:44:26 | 0:44:29 | |
when I read a book which prophesied that composers in the future | 0:44:29 | 0:44:33 | |
would compose directly into sound | 0:44:33 | 0:44:35 | |
instead of using orchestral instruments, you see. | 0:44:35 | 0:44:38 | |
Now, I've made a little loop of tape here | 0:44:38 | 0:44:40 | |
with varying pure tones on it, varying pitches. | 0:44:40 | 0:44:42 | |
Here we are. | 0:44:42 | 0:44:44 | |
ELECTRONIC BURBLING, BEEPING | 0:44:44 | 0:44:48 | |
Good night. | 0:44:50 | 0:44:51 | |
LAUGHTER | 0:44:53 | 0:44:55 | |
APPLAUSE | 0:44:55 | 0:44:57 | |
I'm sorry. | 0:44:57 | 0:44:59 | |
If for no other reason, enduring that face from a reporter... | 0:45:01 | 0:45:05 | |
but mainly, because of her, we have Daft Punk and Basement Jaxx | 0:45:06 | 0:45:10 | |
and Fat Boy Slim and a lot of people whose work I've really enjoyed. | 0:45:10 | 0:45:13 | |
I normally put my people on this wall here, | 0:45:13 | 0:45:16 | |
this sort of semi-wall of shame here. | 0:45:16 | 0:45:18 | |
I'm putting Daphne front and centre. | 0:45:18 | 0:45:19 | |
Well done, Daphne Oram, loving your work. | 0:45:19 | 0:45:22 | |
Who else would you like to add as an unsung scientist? | 0:45:22 | 0:45:24 | |
Well, I'd like to add Athanasius Kircher, | 0:45:24 | 0:45:27 | |
who was a 17th-century Jesuit scholar | 0:45:27 | 0:45:29 | |
who had the most fantastical acoustic devices, | 0:45:29 | 0:45:31 | |
some nice and some unpleasant. | 0:45:31 | 0:45:33 | |
His unpleasant one was the cat piano. | 0:45:33 | 0:45:35 | |
And this was a piano which... | 0:45:35 | 0:45:37 | |
You have a line of about seven cats in little cages | 0:45:37 | 0:45:40 | |
and when you press the keys for the piano, | 0:45:40 | 0:45:42 | |
-it drove a nail into the tail of the cats. -Oh! | 0:45:42 | 0:45:43 | |
These screech and you play tunes on it. | 0:45:43 | 0:45:46 | |
But surely you can only play each note once, twice...? | 0:45:46 | 0:45:48 | |
At some stage, the cat's tail wouldn't take any more, surely? | 0:45:48 | 0:45:51 | |
Well, there's some doubt about whether it was ever made, | 0:45:51 | 0:45:54 | |
but it was done for psychiatric patients, was his idea. | 0:45:54 | 0:45:56 | |
It was meant to shock them out of their condition. | 0:45:56 | 0:45:58 | |
He did actually invent some nice things as well. | 0:45:58 | 0:46:00 | |
Very good. Who would you like to add, Alex? | 0:46:00 | 0:46:02 | |
Music psychology is a very new field, so this is a hard question, | 0:46:02 | 0:46:05 | |
but I decided I'd pick one of our living scientists... | 0:46:05 | 0:46:08 | |
Professor Alf Gabrielsson has spent his whole career | 0:46:08 | 0:46:11 | |
working on music and emotion. | 0:46:11 | 0:46:13 | |
He's retired now, but he worked in Sweden, | 0:46:13 | 0:46:15 | |
and he's got this enormous archive of people's emotional experiences with music. | 0:46:15 | 0:46:18 | |
-Fantastic. What's his name, again? -Alf Gabrielsson. | 0:46:18 | 0:46:21 | |
-And this excellent man here...? -Athanasius Kircher. -Fabulous. | 0:46:21 | 0:46:24 | |
Well worked, Athanasius, with the cat piano. | 0:46:24 | 0:46:26 | |
OK. Has technology in music come too far? | 0:46:26 | 0:46:29 | |
Alok Jha asks if computers are ruining music. | 0:46:29 | 0:46:33 | |
Computers have been used to make music almost from their beginnings. | 0:46:37 | 0:46:41 | |
Synthesisers opened up a whole new world of instrumental sounds. | 0:46:42 | 0:46:46 | |
Sampling brought on the creative cross-fertilisation of genres. | 0:46:50 | 0:46:54 | |
Not even the human voice has escaped the influence of computers. | 0:47:07 | 0:47:10 | |
Thanks to automatic tuning, | 0:47:10 | 0:47:12 | |
you no longer have to be able to sing to record a flawless song. | 0:47:12 | 0:47:17 | |
Estelle Rubio is a singer-songwriter | 0:47:19 | 0:47:22 | |
who teaches studio production at the Tech Music School, London. | 0:47:22 | 0:47:26 | |
-Here it is. -Wow! | 0:47:27 | 0:47:29 | |
I have to say, I was expecting a bigger mixing desk than that. | 0:47:29 | 0:47:32 | |
Well, this is the days of digital, you see. | 0:47:32 | 0:47:34 | |
'Can automatic tuning really turn a bad performer into a good one? | 0:47:34 | 0:47:38 | |
'To put it to the test, we need a bad performance.' | 0:47:38 | 0:47:42 | |
OUT OF TUNE: # Baa, baa, black sheep | 0:47:42 | 0:47:44 | |
# Have you any wool? | 0:47:44 | 0:47:46 | |
# Yes, sir, yes, sir, | 0:47:46 | 0:47:48 | |
# Three bags full... # | 0:47:48 | 0:47:50 | |
Surely THAT is beyond help. | 0:47:50 | 0:47:52 | |
# And one for the dame... # | 0:47:52 | 0:47:53 | |
So, what are we looking at here? We can see the notes I actually sang. | 0:47:53 | 0:47:56 | |
Yes. What we tend to do is go to the nearest note that you were singing. | 0:47:56 | 0:47:59 | |
So, "Baa, baa, BLACK..." | 0:47:59 | 0:48:02 | |
Let's just see. | 0:48:03 | 0:48:04 | |
RECORDING: # Baa, baa, black sheep... # | 0:48:04 | 0:48:07 | |
So, you're going through, | 0:48:07 | 0:48:08 | |
-and you're drawing lines where you want the pitch to be? -Yes. | 0:48:08 | 0:48:11 | |
# Baa, baa, black sheep... # | 0:48:11 | 0:48:13 | |
Automatic tuning literally drags off-key singing back into line. | 0:48:13 | 0:48:16 | |
But does it just polish up something | 0:48:16 | 0:48:18 | |
that shouldn't have been recorded in the first place? | 0:48:18 | 0:48:21 | |
# Yes, sir, yes, sir | 0:48:21 | 0:48:23 | |
# Three bags... # | 0:48:23 | 0:48:25 | |
So, you can see now, you're sounding in-tune, | 0:48:25 | 0:48:27 | |
but in a way, we've lost the essence. | 0:48:27 | 0:48:28 | |
The quality... You've lost the quality of the voice. | 0:48:28 | 0:48:31 | |
Do you think that all of this editing and changing... | 0:48:31 | 0:48:35 | |
Do you think that's cheating a bit? | 0:48:35 | 0:48:37 | |
I still think there are great singers, | 0:48:37 | 0:48:39 | |
but why not let everybody have a chance to make music? | 0:48:39 | 0:48:41 | |
Music's about universal language, it's about sharing... | 0:48:41 | 0:48:44 | |
You know, why can't everybody have a go and play with their voice | 0:48:44 | 0:48:47 | |
and make themselves sound better than they are? | 0:48:47 | 0:48:49 | |
In studio recordings, computers are definitely here to stay. | 0:48:51 | 0:48:55 | |
But there's one area of music | 0:48:55 | 0:48:57 | |
that humans must be able to call their own - composition. | 0:48:57 | 0:49:01 | |
Can computers reach anywhere near the creative heights of composers? | 0:49:01 | 0:49:05 | |
Alexis Kirke is a research fellow | 0:49:06 | 0:49:08 | |
of the Interdisciplinary Centre for Computer Music Research at Plymouth University... | 0:49:08 | 0:49:14 | |
Basically, he makes computers make music. | 0:49:14 | 0:49:16 | |
COMPUTER PLAYS PIANO NOTES | 0:49:16 | 0:49:18 | |
This is a system that I have. I call it IPSIS. | 0:49:18 | 0:49:21 | |
It's a bunch of musical intelligences inside a computer | 0:49:21 | 0:49:26 | |
who sing to each other. | 0:49:26 | 0:49:27 | |
They sing each other very simple tunes, | 0:49:27 | 0:49:30 | |
but when they sing, they pick up each others' tunes. | 0:49:30 | 0:49:34 | |
So, the tunes that they have get bigger, bigger, and bigger | 0:49:34 | 0:49:37 | |
and turn into musical melodies. | 0:49:37 | 0:49:40 | |
Starting with just a single note fed into the computer, | 0:49:40 | 0:49:43 | |
the intelligences build up a tune together. | 0:49:43 | 0:49:46 | |
But do artificial intelligences singing to each other | 0:49:47 | 0:49:50 | |
actually sound any good? | 0:49:50 | 0:49:51 | |
Alexis has a composition called Ash. | 0:49:52 | 0:49:56 | |
COMPUTER PLAYS SIMPLE TUNE AS IF ON PIANO | 0:49:56 | 0:49:59 | |
So, if you close your eyes, | 0:50:03 | 0:50:04 | |
it's like a four-year-old playing piano... | 0:50:04 | 0:50:07 | |
-Yes. -..learning how to play a piano. | 0:50:07 | 0:50:09 | |
Yes, it's very plodding... | 0:50:09 | 0:50:12 | |
Its very, kind of, precise in the rhythm. | 0:50:12 | 0:50:14 | |
No human would play this tune this way. | 0:50:14 | 0:50:17 | |
It might not sound like much, | 0:50:17 | 0:50:19 | |
but to write a pleasant melody from scratch, | 0:50:19 | 0:50:22 | |
computers have to draw on something they just don't have - feelings. | 0:50:22 | 0:50:26 | |
Alexis had to give his algorithms emotions, | 0:50:26 | 0:50:28 | |
but they also need another form of human behaviour. | 0:50:28 | 0:50:31 | |
As well as compose the music, | 0:50:34 | 0:50:35 | |
the system can perform the melodies in an expressive way. | 0:50:35 | 0:50:38 | |
So, there's kind of two layers to this, | 0:50:38 | 0:50:41 | |
there's a layer where it produces the notes, | 0:50:41 | 0:50:44 | |
and there's a layer where it takes those notes | 0:50:44 | 0:50:46 | |
and it tries to express them in a human way. | 0:50:46 | 0:50:51 | |
Although, at the moment, it hardly sets the pulse racing, | 0:50:51 | 0:50:54 | |
the potential for computer algorithms to replace human composers is huge. | 0:50:54 | 0:51:00 | |
I believe in maybe ten years, maybe that soon, | 0:51:00 | 0:51:03 | |
you will have many computers that can compose music | 0:51:03 | 0:51:06 | |
that 80% of us, we won't be able to tell the difference between that | 0:51:06 | 0:51:09 | |
and music composed by a human composer. | 0:51:09 | 0:51:12 | |
Computers are undoubtedly a democratising force in music, | 0:51:13 | 0:51:17 | |
taking the elitism out of composition and performance. | 0:51:17 | 0:51:21 | |
But music is, by nature, an artistic form of human expression, | 0:51:21 | 0:51:25 | |
so is there ultimately any point in taking ourselves out of the equation? | 0:51:25 | 0:51:30 | |
APPLAUSE | 0:51:35 | 0:51:38 | |
Alok, obviously, firstly, thank you so much singing on camera for us, | 0:51:41 | 0:51:45 | |
-which was brave... -I played guitar too. I don't know where that went. | 0:51:45 | 0:51:49 | |
Well, judging by your singing, I can guess where it went. | 0:51:49 | 0:51:52 | |
Did you leave thinking that there was anything in this AI music? | 0:51:52 | 0:51:56 | |
Well, one key question for me is, | 0:51:56 | 0:51:57 | |
"Will any of this ever replace people?" | 0:51:57 | 0:52:00 | |
Whether it's composers or people performing. | 0:52:00 | 0:52:03 | |
And, I think, you know, when it comes to listening to music, | 0:52:03 | 0:52:06 | |
as you've discussed already, you kind of want to think | 0:52:06 | 0:52:09 | |
that someone has slaved away, either producing it, or playing it... | 0:52:09 | 0:52:12 | |
There's some emotion there that's a bits missing. | 0:52:12 | 0:52:15 | |
Now, you can programme computers to have some sort of emotions, | 0:52:15 | 0:52:18 | |
as Alexis Kirke has done... | 0:52:18 | 0:52:20 | |
and you can do a facsimile, but it always will be a bit of a facsimile. | 0:52:20 | 0:52:24 | |
-But that's what -I -think. | 0:52:24 | 0:52:25 | |
In 20 years, 30 years, if this stuff is all over the place | 0:52:25 | 0:52:28 | |
and we're hearing computer-made music and it moves us in the same way, | 0:52:28 | 0:52:31 | |
-then what's the difference? -We can actually test it. | 0:52:31 | 0:52:34 | |
I mean, that was a fairly simple example there, | 0:52:34 | 0:52:36 | |
but we have two pieces of music that we're going to play for you now. | 0:52:36 | 0:52:39 | |
One of them is computer-generated, and one was written by a human. | 0:52:39 | 0:52:42 | |
The... We're not going to tell you which is which. | 0:52:42 | 0:52:45 | |
Let's play the first piece of music. | 0:52:45 | 0:52:46 | |
COURTLY TUNE PLAYS | 0:52:46 | 0:52:49 | |
And let's play the second piece of music... | 0:52:57 | 0:52:59 | |
VERY SIMILAR TUNE PLAYS | 0:52:59 | 0:53:01 | |
Now, we'll take a quick vote on that. You heard them both. | 0:53:10 | 0:53:13 | |
How many of you thought that the computer-written one | 0:53:13 | 0:53:16 | |
was the first piece of music? | 0:53:16 | 0:53:18 | |
I'm with you on that. I thought that was the one. | 0:53:19 | 0:53:22 | |
And then, how many of you thought that the second piece of music...? | 0:53:22 | 0:53:26 | |
The computer-written one was the second piece of music, | 0:53:28 | 0:53:30 | |
that's what you're going for? | 0:53:30 | 0:53:32 | |
OK. The majority, including our experts... | 0:53:32 | 0:53:35 | |
-You're wrong. -LAUGHTER | 0:53:35 | 0:53:37 | |
Ah, but, it's not a fair call, | 0:53:37 | 0:53:39 | |
because that's a style of music that's very, very rule driven. | 0:53:39 | 0:53:42 | |
-Really? -It's really easy to generate something according to rules. | 0:53:42 | 0:53:45 | |
By the way, the "computer-generated piece," as you thought, | 0:53:45 | 0:53:47 | |
that was actually by Bach, just so you know. Just to rub it in. | 0:53:47 | 0:53:51 | |
I actually knew that. That's why I didn't vote. | 0:53:51 | 0:53:53 | |
Because it was cheating. | 0:53:53 | 0:53:54 | |
To balance this debate slightly in favour of science, | 0:53:54 | 0:53:57 | |
we're going to introduce an artist who creates musical works | 0:53:57 | 0:54:00 | |
that simply wouldn't be possible without technology. | 0:54:00 | 0:54:02 | |
Please welcome Imogen Heap, ladies and gentlemen. | 0:54:02 | 0:54:05 | |
APPLAUSE | 0:54:05 | 0:54:06 | |
God love her! | 0:54:06 | 0:54:08 | |
How are you? Now... | 0:54:09 | 0:54:10 | |
I should say... | 0:54:11 | 0:54:12 | |
-..Grammy award-winning artist, Imogen Heap. -That's right. | 0:54:14 | 0:54:17 | |
-And it was actually... The Grammy was in... -Engineering. | 0:54:17 | 0:54:21 | |
..engineering, yeah. | 0:54:21 | 0:54:22 | |
So, you were already working very successfully | 0:54:22 | 0:54:24 | |
with the whole decks and bodies of equipment | 0:54:24 | 0:54:26 | |
-that people would normally have... -Yes. | 0:54:26 | 0:54:29 | |
But you have a new system that you've actually pioneered yourself? | 0:54:29 | 0:54:32 | |
Yes. | 0:54:32 | 0:54:33 | |
In between touring and making albums, | 0:54:33 | 0:54:36 | |
I've been developing these with a team of people... | 0:54:36 | 0:54:38 | |
Just have a quick look here... | 0:54:38 | 0:54:40 | |
Within there, you've got gyroscopes, accelerometers... | 0:54:40 | 0:54:44 | |
What's the cabling here? | 0:54:44 | 0:54:45 | |
-This is the bend sensors. -Bend sensors, so you can... | 0:54:45 | 0:54:48 | |
All of these motions, up, down, left, right... | 0:54:48 | 0:54:52 | |
And also, the stage, I'm mapping, using a Kinect. | 0:54:52 | 0:54:55 | |
-We're in a Kinect here? -Yes. | 0:54:55 | 0:54:56 | |
Well, somebody's found a use for a Kinect, | 0:54:56 | 0:54:58 | |
rather than pretending to be rafting. | 0:54:58 | 0:55:01 | |
And then also, you can flick through different modes, | 0:55:01 | 0:55:04 | |
so you can record with it, you can feed in the sounds... | 0:55:04 | 0:55:07 | |
Yes. Shall I give you an example? | 0:55:07 | 0:55:09 | |
Yeah, I genuinely would love that. A full piece, or just a quick thing? | 0:55:09 | 0:55:12 | |
A quick thing. First of all, I'm just going to demo... | 0:55:12 | 0:55:15 | |
going now into playing...some notes. | 0:55:15 | 0:55:17 | |
NOTES TINKLE | 0:55:17 | 0:55:19 | |
And for those in the audience who can hear, | 0:55:19 | 0:55:21 | |
it's going to the right side and to the left side of the speakers. | 0:55:21 | 0:55:26 | |
And then I can also play a bass, if I wanted to. So... | 0:55:26 | 0:55:30 | |
BASS NOTES PLAY | 0:55:30 | 0:55:32 | |
So, I can change the filter, the kind of...filtering sounds, | 0:55:32 | 0:55:37 | |
and I can mix between two different types of sounds | 0:55:37 | 0:55:40 | |
as I move up and down the scale. | 0:55:40 | 0:55:42 | |
So, it's giving me lots more freedom. I can also take... | 0:55:42 | 0:55:46 | |
I can say, like... | 0:55:46 | 0:55:48 | |
"Dara O'Briain..." | 0:55:48 | 0:55:49 | |
HER SPEECH ECHOES AND DISTORTS | 0:55:49 | 0:55:52 | |
And I could, "La, la, la..." | 0:55:55 | 0:55:57 | |
SPEECH ECHOES | 0:55:57 | 0:55:59 | |
So, I can change the grain...speed | 0:55:59 | 0:56:03 | |
and I can again pan it to the left and the right | 0:56:03 | 0:56:06 | |
and then the volume is here. | 0:56:06 | 0:56:07 | |
But I can map anything to anything. | 0:56:09 | 0:56:10 | |
Wow. OK, well, we'd love to hear something. | 0:56:10 | 0:56:13 | |
Ladies and gentlemen, Imogen Heap. | 0:56:13 | 0:56:15 | |
APPLAUSE | 0:56:15 | 0:56:17 | |
SHE SINGS, SOUNDS ECHO AND DISTORT | 0:56:17 | 0:56:22 | |
TINKLING, THUMPING | 0:56:39 | 0:56:42 | |
SHE WAILS, SOUND ECHOES | 0:56:47 | 0:56:50 | |
ELECTRONIC BUZZING, OWL HOOTS | 0:56:53 | 0:56:55 | |
CHEERING AND APPLAUSE | 0:56:55 | 0:56:58 | |
So... | 0:57:02 | 0:57:04 | |
Obviously, that's only a short taste of Imogen's work. | 0:57:04 | 0:57:07 | |
You can go to her website to find more about her. | 0:57:07 | 0:57:09 | |
I'm sure she has a web presence herself. | 0:57:09 | 0:57:11 | |
It's worth seeing longer pieces to see what she achieves with that. | 0:57:11 | 0:57:14 | |
It's impressive stuff. It's very beautiful stuff. | 0:57:14 | 0:57:17 | |
Now, we were making a slightly less sophisticated instrument | 0:57:17 | 0:57:19 | |
with a 3-D printer. Mark, do you have it there? | 0:57:19 | 0:57:22 | |
-I do. -Lovely. Wow, this is... | 0:57:22 | 0:57:25 | |
-Yes. -Yeah... | 0:57:25 | 0:57:26 | |
This is, apparently... Oh, that's... | 0:57:26 | 0:57:28 | |
It's that. It's a whistle. | 0:57:28 | 0:57:30 | |
It's a penny whistle of some description. Fabulous. Great. | 0:57:30 | 0:57:33 | |
-Have a go. -OK. Grand. -It's not just an ordinary one. | 0:57:33 | 0:57:36 | |
HE BLOWS TUNELESSLY | 0:57:36 | 0:57:38 | |
Wow, yeah, it's not ordinary, is it? It's amazing(!) | 0:57:40 | 0:57:43 | |
It creates some of the most beautiful sounds we've ever had. | 0:57:43 | 0:57:47 | |
Wow, this is how we finish the music show?! With these notes?! | 0:57:47 | 0:57:50 | |
Thanks to all of my guests tonight, | 0:57:50 | 0:57:52 | |
to Alok Jha, Tali Sharot and Mark Miodownik, as ever. | 0:57:52 | 0:57:55 | |
Our special guest James May | 0:57:55 | 0:57:57 | |
and our science gurus Dr Alex Lamont and Professor Trevor Cox, | 0:57:57 | 0:58:00 | |
ladies and gentlemen. | 0:58:00 | 0:58:01 | |
APPLAUSE | 0:58:01 | 0:58:04 | |
And, of course, our thanks go to Imogen Heap. | 0:58:08 | 0:58:11 | |
Now, how to wrap this up? | 0:58:11 | 0:58:13 | |
Cos it's been an 8,000-year journey, to be honest, in terms of music. | 0:58:13 | 0:58:17 | |
We've seen the later stages of it here. | 0:58:17 | 0:58:19 | |
Musical instrument played with the hand alone, | 0:58:19 | 0:58:21 | |
the inside of James May's brain, | 0:58:21 | 0:58:23 | |
we've smashed glasses in the name of science, | 0:58:23 | 0:58:25 | |
so many great things. | 0:58:25 | 0:58:27 | |
But what will stay with me is the fact that this journey started | 0:58:27 | 0:58:30 | |
with a flute made out of bones from a mammoth, | 0:58:30 | 0:58:34 | |
and 8,000 years later, | 0:58:34 | 0:58:37 | |
-we've made this... -HE BLOWS TUNELESSLY | 0:58:37 | 0:58:39 | |
That is as far as it's gone, ladies and gentlemen. | 0:58:39 | 0:58:42 | |
We should be very, deeply impressed by that. | 0:58:42 | 0:58:44 | |
Have a wonderful New Year. We'll see you again. Good night. | 0:58:44 | 0:58:47 | |
Subtitles by Red Bee Media Ltd | 0:59:08 | 0:59:12 |