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ABBY NOYCE: So if we're going to
talk about music and cognition,

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about how we understand music,
how we kind of make sense out

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00:00:27,120 --> 00:00:29,340
of music, we have to
back up a step and say,

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00:00:29,340 --> 00:00:33,870
so what is this music thing?

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00:00:33,870 --> 00:00:34,620
What is music?

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00:00:34,620 --> 00:00:37,995
What defines music as opposed
to other kinds of sounds?

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00:00:41,286 --> 00:00:42,270
AUDIENCE: It's catchy.

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ABBY NOYCE: It's catchy.

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00:00:43,270 --> 00:00:43,769
OK.

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00:00:43,769 --> 00:00:44,800
Some music is catchy.

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AUDIENCE: It's a
string of notes that

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actually sound good together.

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ABBY NOYCE: It's a
stream of notes that

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actually sound good together.

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00:00:50,790 --> 00:00:55,043
AUDIENCE: Generally, if you're
[? in P ?] all of the notes

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00:00:55,043 --> 00:00:58,480
have a common
frequency involved.

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00:00:58,480 --> 00:00:59,105
ABBY NOYCE: OK.

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00:00:59,105 --> 00:01:03,186
They're all like multiples
of some base harmonic.

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00:01:03,186 --> 00:01:05,530
AUDIENCE: There's a
pattern to the tones.

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00:01:05,530 --> 00:01:07,744
ABBY NOYCE: There's a
pattern to the tones.

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00:01:07,744 --> 00:01:08,600
Good.

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00:01:08,600 --> 00:01:09,100
OK.

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00:01:09,100 --> 00:01:10,450
And if you listened
to all of the things

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that we have just
given as definitions,

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00:01:12,074 --> 00:01:16,300
you can probably think of some
example or another of something

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00:01:16,300 --> 00:01:19,219
that claims to be music that
is not true for these things.

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00:01:19,219 --> 00:01:21,010
There's certainly music
that is not catchy.

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00:01:21,010 --> 00:01:24,160
There's certainly music that is
not based on a harmonic scale.

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00:01:24,160 --> 00:01:27,460
There's certainly
all of these things.

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00:01:27,460 --> 00:01:28,150
All right.

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00:01:28,150 --> 00:01:32,980
So we all know that Wikipedia
is not an academic reference,

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00:01:32,980 --> 00:01:39,700
but nonetheless, Wikipedia
defines music as an art form.

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00:01:39,700 --> 00:01:42,930
The medium of which is
sound arranged over time.

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00:01:42,930 --> 00:01:45,100
This is a very broad definition.

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You'll notice that none of
the things that we discussed

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are actually in there.

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00:01:49,420 --> 00:01:54,640
It's merely this organization
of sound over time.

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AUDIENCE: So any sound
basically would be music?

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00:01:57,790 --> 00:02:00,110
ABBY NOYCE: That is organized
over time by somebody.

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00:02:00,110 --> 00:02:01,794
AUDIENCE: Oh, [INAUDIBLE] OK.

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00:02:02,460 --> 00:02:04,585
ABBY NOYCE: Is that a
distinction that makes sense?

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00:02:04,585 --> 00:02:06,500
AUDIENCE: [INAUDIBLE]

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00:02:06,500 --> 00:02:09,617
ABBY NOYCE: So for
example, painting,

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00:02:09,617 --> 00:02:11,950
like the medium is the surface
on which you're painting,

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and the kinds of
pigment and colors,

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things that you're using, right?

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00:02:15,160 --> 00:02:17,370
So Wikipedia says that--

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and I suspect, because this
sounds like a very Wikipedia

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thing that was argued over in
the back channel extensively,

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that there was some
discussion over how can we

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make this definition as
inclusive as possible.

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So they're saying that
the organization of sound

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over time.

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So somebody has got to arrange
the sounds in a certain way.

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Thus it becomes music.

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AUDIENCE: So like [INAUDIBLE].

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Would that be called music?

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ABBY NOYCE: So yeah.

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So one of the things
that I have a problem

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with with this
definition is it doesn't

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make a distinction between music
and, for example, speaking.

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Right.

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I'm clearly organizing
sounds over a period of time

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when I'm sitting
up here talking.

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And I think the general
consensus would be

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that this is not music, right?

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So this is not a
perfect definition

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in any way, shape, or form.

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But it gives us
something to start with.

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And Wikipedia tells
me that the sorts

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of aspects of this
arrangement of sound

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have four key qualities.

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So pitch of the sounds
as they are arranged.

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Rhythm of the sounds.

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So things like tempo
and meter, all of this.

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So we've got pitch, which is
like melody, and harmonies,

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and things like that.

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We've got rhythm and tempo.

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00:03:34,330 --> 00:03:36,070
The dynamics, the
loudness and softness

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of different pieces of it.

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00:03:37,552 --> 00:03:39,010
Who here plays a
musical instrument

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00:03:39,010 --> 00:03:40,880
of one sort or another?

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00:03:40,880 --> 00:03:41,380
OK.

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00:03:41,380 --> 00:03:42,540
Everyone except for me.

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Woo.

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So you guys know
all of this stuff.

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So changing the dynamics
is one of the things that

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defines what makes a
particular piece of music

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00:03:50,260 --> 00:03:52,870
sound in its distinctive way.

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00:03:52,870 --> 00:03:57,190
And finally, and almost kind
of at the bottom compared

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00:03:57,190 --> 00:04:01,170
to all of these others, is the
kind of timbre of the sounds

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00:04:01,170 --> 00:04:02,970
that you can control.

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00:04:02,970 --> 00:04:05,146
So the things that
make a violin playing

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00:04:05,146 --> 00:04:06,520
an A sound different
from a flute

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00:04:06,520 --> 00:04:08,769
playing an A, sound different
from a saxophone playing

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00:04:08,769 --> 00:04:12,940
an A. So it's all
the same pitch,

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00:04:12,940 --> 00:04:17,290
but the timbre, the sounds
of each particular instrument

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00:04:17,290 --> 00:04:18,464
are very different.

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So the other thing I wanted
to talk about really quickly

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00:04:25,560 --> 00:04:27,960
is this idea.

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So we all have
this kind of sense

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that music can convey
emotional content.

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00:04:33,840 --> 00:04:36,100
And we're pretty good with this.

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00:04:36,100 --> 00:04:37,830
We know what a sad
sound sounds like.

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00:04:37,830 --> 00:04:39,950
We know what a happy
song sounds like.

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00:04:39,950 --> 00:04:42,760
We know what an angry
song might sound like.

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00:04:42,760 --> 00:04:43,704
AUDIENCE: [INAUDIBLE]

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ABBY NOYCE: Yes.

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00:04:44,370 --> 00:04:45,540
Thank you.

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00:04:45,540 --> 00:04:48,426
No wonder we're
having difficulties.

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[LAUGHTER]

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AUDIENCE: Great timing.

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ABBY NOYCE: And so there's
been a lot of studies showing

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that with various kinds
of melody instruments

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00:05:01,424 --> 00:05:02,590
that people are really good.

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00:05:02,590 --> 00:05:06,490
If you tell a musician to play
this and play it so it's sad,

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00:05:06,490 --> 00:05:09,130
versus play it so
it's happy, people

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are really good at identifying
what emotion the musician was

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00:05:14,440 --> 00:05:16,870
trying to get across.

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And in my hunt for random
and interesting musical stuff

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today, I found two studies
about just how much subtlety

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00:05:25,570 --> 00:05:29,980
you can get into this idea
of conveying information

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with music.

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And the first one is
these guys went down

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00:05:37,810 --> 00:05:40,890
to just a straight
up drum beat rhythm.

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This is a study by Laukka and
Gabrielsson a few years ago.

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And they had
professional drummers.

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And they had them play
a particular rhythm.

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And they said, play
it so you're happy.

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Play it so it sounds sad.

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Play it so it sounds angry.

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And then they played
these same rhythms

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for a group of subjects,
probably undergrads.

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They're at a university.

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And they said, rate this.

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00:06:07,990 --> 00:06:11,740
Rate on a scale of 1 to 10 how
happy, how angry, how fearful,

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or how sad it is.

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00:06:15,840 --> 00:06:21,320
So here are some drumbeat clips
for you guys to listen to.

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00:06:21,320 --> 00:06:24,350
Tell me what you
think this one is.

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00:06:24,350 --> 00:06:28,550
AUDIENCE: [INAUDIBLE]
that'll screw up the feed.

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00:06:28,550 --> 00:06:31,972
ABBY NOYCE: It shouldn't,
because this isn't streaming.

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00:06:31,972 --> 00:06:34,330
I think it's just an MP3.

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AUDIENCE: Are you sure?

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00:06:35,842 --> 00:06:36,550
ABBY NOYCE: Load.

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00:06:36,550 --> 00:06:38,995
[DRUMS]

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Happy, sad, angry, fearful?

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AUDIENCE: Happy.

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ABBY NOYCE: Anyone
feel otherwise?

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AUDIENCE: Happy.

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00:06:59,471 --> 00:07:00,220
ABBY NOYCE: Happy?

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00:07:00,220 --> 00:07:01,890
Bum-ba-da-dum.

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00:07:01,890 --> 00:07:02,390
OK.

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So there's one.

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00:07:08,160 --> 00:07:11,118
[CYMBALS]

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ABBY NOYCE: So it's
the same base rhythm

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being played differently.

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All right.

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00:07:32,700 --> 00:07:34,200
So which emotion is this?

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AUDIENCE: That
sounds sad or solemn.

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00:07:35,700 --> 00:07:36,795
AUDIENCE: I'd say solemn.

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00:07:36,795 --> 00:07:37,840
AUDIENCE: I'm going with sad.

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00:07:37,840 --> 00:07:38,890
ABBY NOYCE: Solemn or sad.

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AUDIENCE: Sad, sad, sad.

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ABBY NOYCE: How about this one?

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[DRUM BEAT]

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AUDIENCE: [INAUDIBLE]

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00:08:08,990 --> 00:08:09,740
ABBY NOYCE: Angry?

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00:08:09,740 --> 00:08:11,150
AUDIENCE: It sounds happy to me.

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00:08:11,150 --> 00:08:11,900
ABBY NOYCE: Happy?

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00:08:11,900 --> 00:08:13,067
AUDIENCE: [INAUDIBLE] to me.

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ABBY NOYCE: It sounds like what?

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AUDIENCE: Like expressive.

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00:08:15,714 --> 00:08:17,380
AUDIENCE: It sounds
[INAUDIBLE] neutral.

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00:08:17,380 --> 00:08:20,420
ABBY NOYCE: It sounds neutral?

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00:08:20,420 --> 00:08:22,620
AUDIENCE: Like something
to look forward to.

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00:08:22,620 --> 00:08:26,830
ABBY NOYCE: Like
anticipatory sort of?

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00:08:26,830 --> 00:08:28,062
OK.

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00:08:28,062 --> 00:08:29,886
AUDIENCE: So it
could be fearful.

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00:08:29,886 --> 00:08:31,274
AUDIENCE: That could be fearful.

187
00:08:31,274 --> 00:08:32,440
ABBY NOYCE: What's this one?

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00:08:32,440 --> 00:08:34,940
[DRUM BEAT]

189
00:08:43,745 --> 00:08:45,685
[LAUGHTER]

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AUDIENCE: I don't know.

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00:08:48,060 --> 00:08:50,790
AUDIENCE: I think
extremely happy or angry.

192
00:08:50,790 --> 00:08:52,087
ABBY NOYCE: Happy or angry?

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00:08:52,087 --> 00:08:53,420
AUDIENCE: I thought [INAUDIBLE].

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00:08:53,420 --> 00:08:54,045
AUDIENCE: Yeah.

195
00:08:54,045 --> 00:08:55,340
ABBY NOYCE: All right.

196
00:08:55,340 --> 00:08:59,150
So let's see what
these actually were.

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00:08:59,150 --> 00:09:01,270
So those were happy,
sad, angry, and fearful.

198
00:09:01,270 --> 00:09:02,395
AUDIENCE: That was fearful?

199
00:09:02,395 --> 00:09:03,520
AUDIENCE: That was fearful?

200
00:09:03,520 --> 00:09:08,185
ABBY NOYCE: Interestingly
enough, we got the first two.

201
00:09:08,185 --> 00:09:10,310
Like everybody pretty much
agreed on the first two.

202
00:09:10,310 --> 00:09:14,580
And then the last two we were
a little bit more varied on.

203
00:09:14,580 --> 00:09:17,140
And these guys actually--

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00:09:17,140 --> 00:09:17,640
yes.

205
00:09:17,640 --> 00:09:20,270
They threw in here a graph
of the data these guys got.

206
00:09:20,270 --> 00:09:25,250
So, again, they had
people rate each sample

207
00:09:25,250 --> 00:09:33,140
based on how well they thought
it fit a particular emotion.

208
00:09:33,140 --> 00:09:36,470
So when the musician was
trying to play happiness,

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00:09:36,470 --> 00:09:41,440
people rated happy the highest
emotion, and others lower.

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00:09:41,440 --> 00:09:42,519
Likewise for sadness.

211
00:09:42,519 --> 00:09:43,310
Likewise for anger.

212
00:09:43,310 --> 00:09:44,520
Likewise for fear.

213
00:09:44,520 --> 00:09:46,020
So the thing that's
interesting here

214
00:09:46,020 --> 00:09:48,710
is that those dark blue
bars are the places where

215
00:09:48,710 --> 00:09:51,730
one is actually significantly
different from the others

216
00:09:51,730 --> 00:09:54,020
in the statistical
sense, so that it's

217
00:09:54,020 --> 00:09:56,420
significantly different.

218
00:09:56,420 --> 00:10:01,700
So fear was rated
significantly higher

219
00:10:01,700 --> 00:10:03,140
than all of the
other categories.

220
00:10:05,870 --> 00:10:08,720
The fear sample was
rated as more fearful

221
00:10:08,720 --> 00:10:10,700
than all of the
other categories.

222
00:10:10,700 --> 00:10:16,850
And also then the
sample was rated for all

223
00:10:16,850 --> 00:10:18,080
of the other categories.

224
00:10:18,080 --> 00:10:19,580
It was also rated
as more fearful

225
00:10:19,580 --> 00:10:21,360
than all of the other samples.

226
00:10:21,360 --> 00:10:23,120
So this is a really
solid result.

227
00:10:23,120 --> 00:10:26,540
And it's cool because it's
this really minimalist input

228
00:10:26,540 --> 00:10:29,420
that they're using, these really
basic samples that are just

229
00:10:29,420 --> 00:10:36,230
basically only varying by
tempo and by dynamic versus

230
00:10:36,230 --> 00:10:38,540
like a melodic
instrument, which has

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00:10:38,540 --> 00:10:41,508
a lot more ways of variation.

232
00:10:41,508 --> 00:10:43,424
AUDIENCE: Do you think
it could have something

233
00:10:43,424 --> 00:10:45,435
to do with the culture?

234
00:10:45,435 --> 00:10:46,310
ABBY NOYCE: It might.

235
00:10:46,310 --> 00:10:48,268
AUDIENCE: If they expanded
the sample to people

236
00:10:48,268 --> 00:10:50,030
from different cultures--

237
00:10:50,030 --> 00:10:52,250
ABBY NOYCE: Well, so we
have a cross-culture here,

238
00:10:52,250 --> 00:10:54,375
because we just did it on
a bunch of American kids.

239
00:10:54,375 --> 00:10:56,041
And they did it.

240
00:10:56,041 --> 00:10:56,540
Oopsala.

241
00:10:56,540 --> 00:10:57,530
Where's Oopsala.

242
00:10:57,530 --> 00:11:04,328
I'm guessing somewhere in
like Scandinavia, right?

243
00:11:04,328 --> 00:11:05,300
AUDIENCE: Oopsala.

244
00:11:05,300 --> 00:11:06,759
ABBY NOYCE: Anyone know?

245
00:11:06,759 --> 00:11:07,300
I don't know.

246
00:11:07,300 --> 00:11:09,090
My guess is it's like
Sweden or somewhere.

247
00:11:09,090 --> 00:11:09,860
AUDIENCE: Google it.

248
00:11:09,860 --> 00:11:10,750
ABBY NOYCE: We can Google it.

249
00:11:10,750 --> 00:11:11,116
AUDIENCE: Google.

250
00:11:11,116 --> 00:11:11,850
Google.

251
00:11:11,850 --> 00:11:13,060
ABBY NOYCE: Where is Oopsala?

252
00:11:16,480 --> 00:11:16,980
Sweden.

253
00:11:16,980 --> 00:11:17,450
AUDIENCE: Sweden!

254
00:11:17,450 --> 00:11:18,400
ABBY NOYCE: All right.

255
00:11:18,400 --> 00:11:21,140
So there's two
samples right there.

256
00:11:21,140 --> 00:11:23,650
And you can argue that
Northeastern America

257
00:11:23,650 --> 00:11:27,220
and Northwestern Europe
are pretty closely

258
00:11:27,220 --> 00:11:28,080
related cultures.

259
00:11:28,080 --> 00:11:30,538
It would be interesting to run
it somewhere very different.

260
00:11:34,600 --> 00:11:35,360
OK.

261
00:11:35,360 --> 00:11:36,943
And the other one I
wanted to show you

262
00:11:36,943 --> 00:11:38,585
guys is this other
really cool study.

263
00:11:38,585 --> 00:11:43,640
And this is a German group
that were doing an ERP study.

264
00:11:43,640 --> 00:11:45,800
So they're using an EEG
cap with the electrodes

265
00:11:45,800 --> 00:11:48,620
to measure the electrical
activity of the brain.

266
00:11:48,620 --> 00:11:50,600
And they're not just
going for emotions.

267
00:11:50,600 --> 00:11:53,900
They're trying to see if
music can convey some really

268
00:11:53,900 --> 00:11:56,530
kind of sophisticated concepts.

269
00:11:56,530 --> 00:11:58,910
The example they use in
their paper is wideness.

270
00:11:58,910 --> 00:12:01,442
Can music convey this
idea of wideness.

271
00:12:01,442 --> 00:12:02,900
So what they did
is they had people

272
00:12:02,900 --> 00:12:08,570
listen to a sentence, which was
either related or unrelated.

273
00:12:08,570 --> 00:12:11,070
And these are translated, since
the originals are in German.

274
00:12:11,070 --> 00:12:13,430
So the related sentence
would be "The gaze

275
00:12:13,430 --> 00:12:15,200
wandered into the distance."

276
00:12:15,200 --> 00:12:17,210
And the unrelated
sentence would be,

277
00:12:17,210 --> 00:12:20,330
"The manacles allow
only little movement."

278
00:12:20,330 --> 00:12:23,680
And you can see those are
just the sonograms of that,

279
00:12:23,680 --> 00:12:25,470
numbered.

280
00:12:25,470 --> 00:12:28,250
So showing how the sound--

281
00:12:28,250 --> 00:12:31,510
I think those are just
dynamic graphs actually.

282
00:12:31,510 --> 00:12:36,680
Anyway, if you look at the
graph on the upper right there,

283
00:12:36,680 --> 00:12:39,080
then you can see the purple
line and the blue line

284
00:12:39,080 --> 00:12:45,020
are the EEG measurements
of the unrelated prime

285
00:12:45,020 --> 00:12:46,760
and the related prime.

286
00:12:46,760 --> 00:12:48,860
And in particular, you
can see that the blue line

287
00:12:48,860 --> 00:12:51,530
and the purple line follow each
other exactly for the first

288
00:12:51,530 --> 00:12:53,630
like 300 milliseconds.

289
00:12:53,630 --> 00:12:55,310
And then that N400.

290
00:12:55,310 --> 00:12:59,282
Remember, because negative
is up on this graph.

291
00:12:59,282 --> 00:13:01,490
So that spike where it goes
back towards the negative

292
00:13:01,490 --> 00:13:05,630
at about 400 milliseconds after
the stimulus is different.

293
00:13:05,630 --> 00:13:08,375
It's bigger for
the unrelated prime

294
00:13:08,375 --> 00:13:09,500
than for the related prime.

295
00:13:09,500 --> 00:13:11,190
The related prime
has a smaller spike.

296
00:13:11,190 --> 00:13:12,940
And so they looked at
that, and they said,

297
00:13:12,940 --> 00:13:16,010
OK, what about for music?

298
00:13:16,010 --> 00:13:19,320
And they played two
musical samples.

299
00:13:19,320 --> 00:13:23,540
One of which they claim conveys
the concept of wildness.

300
00:13:23,540 --> 00:13:26,010
[MUSIC PLAYING]

301
00:13:33,420 --> 00:13:35,410
AUDIENCE: Very Disney.

302
00:13:35,410 --> 00:13:40,665
ABBY NOYCE: And one of
which they claim does not.

303
00:13:40,665 --> 00:13:42,790
And you can argue all you
like about whether or not

304
00:13:42,790 --> 00:13:43,840
these are good primes.

305
00:13:43,840 --> 00:13:46,295
[MUSIC PLAYING]

306
00:13:46,295 --> 00:13:48,259
[GIGGLING]

307
00:13:56,115 --> 00:13:59,418
AUDIENCE: Accordions.

308
00:13:59,418 --> 00:14:00,043
AUDIENCE: Wait.

309
00:14:00,043 --> 00:14:02,036
People still actually
play accordions.

310
00:14:02,036 --> 00:14:02,661
AUDIENCE: Yeah.

311
00:14:02,661 --> 00:14:03,286
AUDIENCE: Yeah.

312
00:14:03,286 --> 00:14:03,787
Obviously.

313
00:14:03,787 --> 00:14:05,744
ABBY NOYCE: And so they
found two music samples

314
00:14:05,744 --> 00:14:07,500
that were the same
length that didn't show

315
00:14:07,500 --> 00:14:09,597
dramatic dynamic differences.

316
00:14:09,597 --> 00:14:11,430
Although there's
definitely patterns in them

317
00:14:11,430 --> 00:14:12,110
that you can see.

318
00:14:12,110 --> 00:14:13,984
This one gets much louder
at the end in a way

319
00:14:13,984 --> 00:14:16,314
that the unrelated prime--

320
00:14:16,314 --> 00:14:17,790
AUDIENCE: She's still talking.

321
00:14:17,790 --> 00:14:20,220
ABBY NOYCE: --doesn't.

322
00:14:20,220 --> 00:14:22,570
And, again, the same thing.

323
00:14:22,570 --> 00:14:28,157
They measured the event revoked
event response potential

324
00:14:28,157 --> 00:14:29,490
in response to these two primes.

325
00:14:29,490 --> 00:14:33,780
So if they had people
listen to the Strauss piece

326
00:14:33,780 --> 00:14:36,090
and then asked them whether
it was related or unrelated

327
00:14:36,090 --> 00:14:38,710
to wideness, then
they found, again,

328
00:14:38,710 --> 00:14:42,296
that this N400 is smaller
in the related case

329
00:14:42,296 --> 00:14:43,420
than in the unrelated case.

330
00:14:43,420 --> 00:14:44,520
And what's interesting
is that that's

331
00:14:44,520 --> 00:14:47,040
the exact same pattern they
found for the linguistic prime.

332
00:14:50,700 --> 00:14:52,860
And one of the big
confounds in this study

333
00:14:52,860 --> 00:14:56,940
is that they are asking
people to consider

334
00:14:56,940 --> 00:15:00,510
whether the prime, whether the
sentence or the musical piece,

335
00:15:00,510 --> 00:15:03,340
is or is not related
to the concept.

336
00:15:03,340 --> 00:15:05,940
So the difference
here could just

337
00:15:05,940 --> 00:15:12,000
be falling out to people's
difference in response,

338
00:15:12,000 --> 00:15:14,430
and people's difference
in perception

339
00:15:14,430 --> 00:15:17,700
as they judge it after the fact,
and not to an actual difference

340
00:15:17,700 --> 00:15:20,720
in seeing this as more
wide or less wide,

341
00:15:20,720 --> 00:15:24,930
but having decided that it
was more wide or less wide.

342
00:15:24,930 --> 00:15:27,550
So it's not the world's
best control study.

343
00:15:27,550 --> 00:15:32,070
But it's nonetheless a
really interesting result.

344
00:15:32,070 --> 00:15:33,600
And I'm moderately impressed.

345
00:15:33,600 --> 00:15:35,940
I wouldn't have thought
you could pull out

346
00:15:35,940 --> 00:15:39,510
something with that
level of semantic content

347
00:15:39,510 --> 00:15:40,650
from a musical sample.

348
00:15:40,650 --> 00:15:44,000
So I thought that
was really cool.

349
00:15:44,000 --> 00:15:44,500
Yes.

350
00:15:44,500 --> 00:15:46,541
AUDIENCE: So they asked
them to consider wideness

351
00:15:46,541 --> 00:15:47,490
before they listened?

352
00:15:47,490 --> 00:15:50,470
ABBY NOYCE: They played them
the sentence, or the sample.

353
00:15:50,470 --> 00:15:53,891
And then they put the word on
the screen in front of them

354
00:15:53,891 --> 00:15:56,390
and said, was the thing you
just heard related to this word?

355
00:15:56,390 --> 00:15:57,970
Yes or no?

356
00:15:57,970 --> 00:16:00,430
So people didn't
have wideness in mind

357
00:16:00,430 --> 00:16:02,920
when they were listening
to these things.

358
00:16:02,920 --> 00:16:08,330
I think the timescale
on the sample is--

359
00:16:08,330 --> 00:16:08,830
yeah.

360
00:16:08,830 --> 00:16:11,470
This is measured from when
they see the word that they're

361
00:16:11,470 --> 00:16:12,507
asked to judge.

362
00:16:12,507 --> 00:16:14,590
So it's when they're making
that judgment decision

363
00:16:14,590 --> 00:16:16,076
about related or unrelated.

364
00:16:16,076 --> 00:16:17,950
And you see this difference
whether the thing

365
00:16:17,950 --> 00:16:20,460
that they're considering
is a musical prime

366
00:16:20,460 --> 00:16:22,300
or a linguistic prime.

367
00:16:22,300 --> 00:16:27,250
But the difference could be an
artifact of the decision making

368
00:16:27,250 --> 00:16:31,432
process, rather than an artifact
of the original perception,

369
00:16:31,432 --> 00:16:32,890
which they're kind
of fuzzy around.

370
00:16:36,012 --> 00:16:36,970
What do you guys think?

371
00:16:36,970 --> 00:16:38,955
Was the Strauss sample wide?

372
00:16:38,955 --> 00:16:40,787
Do you think it sounded wide?

373
00:16:40,787 --> 00:16:43,370
AUDIENCE: I think if you hadn't
mentioned the wideness before,

374
00:16:43,370 --> 00:16:44,750
[INAUDIBLE]

375
00:16:44,750 --> 00:16:46,910
ABBY NOYCE: It would
be a better sample?

376
00:16:46,910 --> 00:16:49,360
Yes.

377
00:16:49,360 --> 00:16:50,440
This is probably true.

378
00:16:50,440 --> 00:16:53,010
AUDIENCE: I was practically
listening for the wideness.

379
00:16:53,010 --> 00:16:55,600
ABBY NOYCE: Do you think the
Strauss sample sounded wider

380
00:16:55,600 --> 00:16:57,070
than the--

381
00:16:57,070 --> 00:16:58,930
who else was it--

382
00:16:58,930 --> 00:17:02,130
[INAUDIBLE] sample?

383
00:17:02,130 --> 00:17:03,252
Did it sound wider?

384
00:17:03,252 --> 00:17:05,474
AUDIENCE: Yes.

385
00:17:05,474 --> 00:17:08,015
ABBY NOYCE: Is that because you
were expecting it to be wide?

386
00:17:08,015 --> 00:17:11,340
AUDIENCE: It kind of is
hard to define wideness.

387
00:17:11,340 --> 00:17:14,190
ABBY NOYCE: Yeah.

388
00:17:14,190 --> 00:17:15,281
Definitely.

389
00:17:18,720 --> 00:17:21,900
How would you define wideness
in music, [INAUDIBLE]??

390
00:17:21,900 --> 00:17:24,652
How would you express
wideness in music?

391
00:17:24,652 --> 00:17:27,135
So Strauss does it with
this big crescendoing thing.

392
00:17:27,135 --> 00:17:27,760
AUDIENCE: Yeah.

393
00:17:27,760 --> 00:17:29,832
So more dramatic I guess.

394
00:17:29,832 --> 00:17:30,540
ABBY NOYCE: Yeah.

395
00:17:35,798 --> 00:17:36,730
Cool.

396
00:17:36,730 --> 00:17:38,188
AUDIENCE: I think
they expressed it

397
00:17:38,188 --> 00:17:40,698
by starting with something
that wasn't wide.

398
00:17:40,698 --> 00:17:47,780
So the less voluminous,
the less dynamics,

399
00:17:47,780 --> 00:17:51,250
and the less instruments
were participating in it.

400
00:17:51,250 --> 00:17:53,578
It's sort of the
contrast so that when

401
00:17:53,578 --> 00:17:56,070
you reach the peak of the
crescendo you say, wow.

402
00:17:59,465 --> 00:18:01,410
ABBY NOYCE: OK.

403
00:18:01,410 --> 00:18:02,280
Yeah.

404
00:18:02,280 --> 00:18:07,080
So it definitely like expands,
like the dynamic range goes up.

405
00:18:07,080 --> 00:18:07,720
I don't know.

406
00:18:07,720 --> 00:18:08,550
Does it make you
feel like you're

407
00:18:08,550 --> 00:18:09,780
looking out on an open vista?

408
00:18:09,780 --> 00:18:11,196
If you had to
animate, if you were

409
00:18:11,196 --> 00:18:12,687
like doing Fantasia
3 or something

410
00:18:12,687 --> 00:18:15,270
and trying to animate a scene
to go with that particular piece

411
00:18:15,270 --> 00:18:18,134
of music, what would you do?

412
00:18:18,134 --> 00:18:19,125
AUDIENCE: [INAUDIBLE]

413
00:18:19,125 --> 00:18:19,750
ABBY NOYCE: No?

414
00:18:19,750 --> 00:18:21,708
Yes?

415
00:18:21,708 --> 00:18:27,054
AUDIENCE: Walking on a dark
street with a random guy

416
00:18:27,054 --> 00:18:28,512
playing the accordion.

417
00:18:28,512 --> 00:18:30,456
[LAUGHTER]

418
00:18:30,456 --> 00:18:32,666
ABBY NOYCE: For the second one?

419
00:18:32,666 --> 00:18:34,062
Or for the Strauss.

420
00:18:34,062 --> 00:18:35,360
AUDIENCE: For the second one.

421
00:18:35,360 --> 00:18:35,650
ABBY NOYCE: OK.

422
00:18:35,650 --> 00:18:37,717
AUDIENCE: I was thinking
of walking [INAUDIBLE]

423
00:18:37,717 --> 00:18:38,551
[INTERPOSING VOICES]

424
00:18:38,551 --> 00:18:39,175
AUDIENCE: Yeah.

425
00:18:39,175 --> 00:18:39,847
AUDIENCE: Yeah.

426
00:18:39,847 --> 00:18:44,369
I mean, like, if no one else
was there except him and you--

427
00:18:44,369 --> 00:18:44,994
AUDIENCE: Yeah.

428
00:18:44,994 --> 00:18:46,070
And just [INAUDIBLE].

429
00:18:46,070 --> 00:18:48,110
AUDIENCE: Just
walking [INAUDIBLE]..

430
00:18:48,110 --> 00:18:49,400
AUDIENCE: There you go.

431
00:18:49,400 --> 00:18:50,290
AUDIENCE: The first one
to be walking [INAUDIBLE]..

432
00:18:50,290 --> 00:18:51,840
ABBY NOYCE: All right.