Name: ギル・ワインバーグ教授"ジョージア工科大学でのロボット音楽活動」｜Googleで講演 (Professor Gil Weinberg: "Robotic Musicianship at Georgia Tech" | Talks at Google)
Uploaded: 2021-01-14T05:39:26.000Z
Duration: 1 h 6 min 15 s
Description: VoiceTubeの動画で発音を聞きながら英語表現を覚えよう！学べる英語：

It's my pleasure to introduce Gil Weinberg.

He's a professor at Georgia Tech for the Center of Music

And I went to Georgia Tech a long, long time ago

and we didn't have a music department back then.

So when I visited recently, the folks I was meeting with in ECE

doing some really cool stuff with interactive computing

So building machines that you can interact with,

like the kind of thing I'm thinking about,

And he's going to talk about that in many other things

So I'm going to talk about three or four main projects.

Only three of them I showed in these slides.

We did the project which we just finished and I have some very,

in computation or in robotics, I was a musician and still am.

And I was always fascinated by playing in a group.

By being constantly ready to change what I'm doing.

Improvising in a group, a visual cues, auditory cues, of course.

So when I started to be interested in robotics,

Before I show you some of the efforts that I did,

maybe I'll show a short clip of me playing with a trumpet

player and trying to see the kind of experiences

So I think you've seen a lot of eye contact,

trying to build a motif that I'm not sure what is going to be

and trying to create something interesting with them

And the first robots that I tried to develop it

But what I wanted to do is to have the robot understand music

was to create robots that listen like humans,

Because I felt that if I want to push what music

is about through new, novel improvisation

I first have to have connection between humans and robots,

and that's why there is the listening like human part.

Only then would I be able to start to make the robot

play like a machine in order to create this kind of connection

that probably many of you are familiar with.

maybe the first simple thing that I can make him do

is understand the beat of the music that I play.

And here we use auto-correlation and self-similarity algorithms.

You see the time is both on the x and on the y.

And you see that it's symmetric and by comparing

can try to find sections that are similar

But what we try to do is to actually have it in real time.

And you see here my student Scott Driscoll

used this algorithm based on Davies and Plumbley

sophisticated because it's not just analyzing the beat in Bach

or in the Beatles-- Scott is playing in real-time so he

is trying to get the beat, but then with Haile,

doing to what Haile-- Haile is a robot-- and back and forth.

So it's a little more complicated you see.

Sometimes they escape from the beat and get back to the beat.

So as you can see, it loses it, it gets it back.

I think in a second, it will play slower which

is to have the robot understand other things at a high level

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ギル・ワインバーグ教授"ジョージア工科大学でのロボット音楽活動」｜Googleで講演 (Professor Gil Weinberg: "Robotic Musicianship at Georgia Tech" | Talks at Google)

rhythm

audience

create

beat