How AI could compose a personalized soundtrack to your life Pierre Barreau

About two and a half years ago,
I watched this movie called “Her.”

And it features Samantha,
a superintelligent form of AI

that cannot take physical form.

And because she can’t
appear in photographs,

Samantha decides to write a piece of music

that will capture a moment of her life
just like a photograph would.

As a musician and an engineer,
and someone raised in a family of artists,

I thought that this idea of musical
photographs was really powerful.

And I decided to create an AI composer.

Her name is AIVA,
and she’s an artificial intelligence

that has learned the art
of music composition

by reading over 30,000 scores
of history’s greatest.

So here’s what one score
looks like to the algorithm

in a matrix-like representation.

And here’s what 30,000 scores,

written by the likes
of Mozart and Beethoven,

look like in a single frame.

So, using deep neural networks,
AIVA looks for patterns in the scores.

And from a couple of bars
of existing music,

it actually tries to infer what notes
should come next in those tracks.

And once AIVA gets good
at those predictions,

it can actually build a set
of mathematical rules

for that style of music

in order to create
its own original compositions.

And in a way, this is kind of
how we, humans, compose music, too.

It’s a trial-and-error process,

during which we may not
get the right notes all the time.

But we can correct ourselves,

either with our musical ear
or our musical knowledge.

But for AIVA, this process
is taken from years and years of learning,

decades of learning as an artist,
as a musician and a composer,

down to a couple of hours.

But music is also a supersubjective art.

And we needed to teach AIVA

how to compose the right music
for the right person,

because people have different preferences.

And to do that, we show to the algorithm
over 30 different category labels

for each score in our database.

So those category labels are like mood

or note density or composer
style of a piece

or the epoch during which it was written.

And by seeing all this data,

AIVA can actually respond
to very precise requirements.

Like the ones, for example,
we had for a project recently,

where we were commissioned
to create a piece

that would be reminiscent
of a science-fiction film soundtrack.

And the piece that was created
is called “Among the Stars”

and it was recorded
with CMG Orchestra in Hollywood,

under great conductor John Beal,

and this is what they
recorded, made by AIVA.

(Music)

(Music ends)

What do you think?

(Applause)

Thank you.

So, as you’ve seen, AI can create
beautiful pieces of music,

and the best part of it

is that humans can actually
bring them to life.

And it’s not the first time in history

that technology has augmented
human creativity.

Live music was almost always
used in silent films

to augment the experience.

But the problem with live music
is that it didn’t scale.

It’s really hard to cram a full symphony
into a small theater,

and it’s really hard to do that
for every theater in the world.

So when music recording
was actually invented,

it allowed content creators,
like film creators,

to have prerecorded and original music

tailored to each and every frame
of their stories.

And that was really
an enhancer of creativity.

Two and a half years ago,
when I watched this movie “Her,”

I thought to myself
that personalized music

would be the next single biggest change
in how we consume and create music.

Because nowadays, we have
interactive content, like video games,

that have hundreds of hours
of interactive game plays,

but only two hours of music, on average.

And it means that the music
loops and loops and loops

over and over again,
and it’s not very immersive.

So what we’re working on
is to make sure that AI can compose

hundreds of hours of personalized music

for those use cases
where human creativity doesn’t scale.

And we don’t just want
to do that for games.

Beethoven actually wrote a piece
for his beloved, called “Für Elise,”

and imagine if we could
bring back Beethoven to life.

And if he was sitting next to you,
composing a music for your personality

and your life story.

Or imagine if someone like
Martin Luther King, for example,

had a personalized AI composer.

Maybe then we would remember

“I Have a Dream” not only
as a great speech,

but also as a great piece of music,
part of our history,

and capturing Dr. King’s ideals.

And this is our vision at AIVA:

to personalize music
so that each and every one of you

and every individual in the world

can have access to a personalized
live soundtrack,

based on their story
and their personality.

So this moment here together at TED
is now part of our life story.

So it only felt fitting that AIVA
would compose music for this moment.

And that’s exactly what we did.

So my team and I worked on biasing AIVA
on the style of the TED jingle,

and on music that makes us feel
a sense of awe and wonder.

And the result is called
“The Age of Amazement.”

Didn’t take an AI to figure that one out.

(Laughter)

And I couldn’t be more proud
to show it to you,

so if you can, close your eyes
and enjoy the music.

Thank you very much.

(Music)

[The Age of Amazement
Composed by AIVA]

(Music ends)

This was for all of you.

Thank you.

(Applause)

大约两年半前,
我看了一部叫《她》的电影。

它以萨曼莎为特色,这
是一种无法以物理形式出现的人工智能的超级智能

形式。

因为她不能
出现在照片中,

萨曼莎决定写一首音乐

,像照片一样捕捉她生命中的每一刻

作为一名音乐家和工程师,
以及在一个艺术家家庭长大的人,

我认为这种音乐
照片的想法非常强大。

我决定创建一个 AI 作曲家。

她的名字叫 AIVA
,她是一个人工智能

通过阅读 30,000
多首历史上最伟大的乐谱来学习作曲艺术。

所以这是一个分数

在类似矩阵的表示中的算法的样子。

是由
莫扎特和贝多芬

等人创作的 30,000 首乐谱在单帧中的样子。

因此,AIVA 使用深度神经网络
在分数中寻找模式。

从现有音乐的几个小节
中,

它实际上试图推断
这些音轨中接下来应该出现什么音符。

一旦 AIVA
擅长这些预测,

它实际上可以为这种音乐风格建立
一套数学规则

,以创作
自己的原创作品。

在某种程度上,这也是
我们人类创作音乐的方式。

这是一个反复试验的过程,

在此过程中,我们可能无法
始终得到正确的笔记。

但是我们

可以用我们的音乐耳朵
或我们的音乐知识来纠正自己。

但对于 AIVA 来说,这个
过程需要多年的学习,

几十年来作为艺术家
、音乐家和作曲家的学习,

缩短到几个小时。

但音乐也是一种超主观的艺术。

我们需要教 AIVA

如何为合适的人创作合适的音乐

因为人们有不同的偏好。

为此,我们向算法展示

了数据库中每个分数的 30 多个不同类别标签。

因此,这些类别标签就像一首曲子的情绪

或音符密度或作曲家
风格

或写作的时代。

通过查看所有这些数据,

AIVA 实际上可以
响应非常精确的要求。

就像那些,例如,
我们最近有一个项目

,我们被
委托创作一部

让人
想起科幻电影配乐的作品。

创作的作品
名为“Among the Stars”

,由
好莱坞的 CMG Orchestra 录制,

由伟大的指挥家 John Beal 指挥

,这就是他们
录制的,由 AIVA 制作。

(音乐)

(音乐结束)

你怎么看?

(掌声)

谢谢。

所以,正如你所看到的,人工智能可以创造出
美妙的音乐,

其中最好的部分

是人类实际上可以
将它们变为现实。

这不是历史上第一次

技术增强了
人类的创造力。 无声电影

中几乎总是使用现场音乐

来增强体验。

但现场音乐的问题
在于它没有规模化。

把一部完整的交响乐
塞进一个小

剧院真的很难,
世界上每个剧院都很难做到这一点。

因此,当音乐
录音真正被发明时,

它允许内容创作者,
如电影创作者,

为他们故事的每一帧量身定制预先录制的原创音乐

这确实
是创造力的增强剂。

两年半前,
当我看这部电影《她》时,

我心想
,个性化音乐

将是
我们消费和创作音乐方式的下一个最大变化。

因为现在,我们有
互动内容,比如视频游戏

,有数百小时
的互动游戏

,但平均只有两个小时的音乐。

这意味着音乐

一遍又一遍地循环,循环,
而且不是很沉浸。

因此,我们
正在努力确保人工智能可以


人类创造力无法扩展的那些用例创作数百小时的个性化音乐。

而且我们不只是想
为游戏这样做。

贝多芬实际上
为他心爱的人写了一首名为“Für Elise”的曲子

,想象一下我们是否可以
让贝多芬复活。

如果他坐在你旁边,
为你的个性和人生故事谱写一首音乐

或者想象一下,如果像
马丁路德金这样的人

拥有一个个性化的人工智能作曲家。

也许那时我们会记住

“我有一个梦想”,不仅
是一场伟大的演讲,

而且是一首伟大的音乐,
是我们历史的一部分,

并体现了金博士的理想。

这就是我们在 AIVA 的愿景

:个性化音乐,
以便

你们每一个人和世界上的每一个人

都可以根据他们的故事和个性获得个性化的
现场配乐

因此,在 TED 的这一刻
现在已经成为我们生活故事的一部分。

因此,AIVA
为这一刻创作音乐只是觉得合适。

这正是我们所做的。

所以我和我的团队致力于让 AIVA 偏向
于 TED 叮当的风格,

以及让我们
感到敬畏和惊奇的音乐。

结果被称为
“惊奇时代”。

没有用人工智能来解决这个问题。

(笑声)

我很自豪
能把它展示给你们看,

所以如果可以的话,
闭上眼睛享受音乐。

非常感谢你。

(音乐)

【AIVA作曲
的惊奇时代】

(音乐结束)

这是给大家的。

谢谢你。

(掌声)