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00:00
Translator: Joseph Geni
Reviewer: Morton Bast
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譯者: Chen-Han Hsiao
審譯者: jimi charlie
00:15
My passions
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我的熱情
00:16
are music, technology and making things.
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是音樂,科技,以及創造東西。
00:20
And it's the combination of these things
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而且就是這些東西的組合
00:23
that has led me to the hobby of sound visualization,
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促使我對聲音的圖像化產生興趣,
00:26
and, on occasion, has led me to play with fire.
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而且,有時,促使我去玩火.
00:30
This is a Rubens' tube. It's one of many I've made over the years,
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這是魯本斯管.近幾些年來我做的其中一個,
00:32
and I have one here tonight.
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今天晚上呢我也帶來了一個.
00:34
It's about an 8-foot-long tube of metal,
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這東西是一支大約8英尺長的金屬管,
00:36
it's got a hundred or so holes on top,
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管上差不多有一百多個小孔,
00:37
on that side is the speaker, and here
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那邊有個喇叭,而這邊呢
00:39
is some lab tubing, and it's connected to this tank
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有一些實驗用的管子,而且是和這個裝滿丙烷
00:41
of propane.
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的容器連接的.
00:44
So, let's fire it up and see what it does.
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那麼,我們現在就把它點燃看看會發生什麼事.
00:53
So let's play a 550-herz frequency
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嗯...我們先試試550赫茲的頻率吧
00:55
and watch what happens.
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看看會有什麼效果.
00:56
(Frequency)
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(頻率)
01:05
Thank you. (Applause)
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謝謝.(觀衆鼓掌)
01:07
It's okay to applaud the laws of physics,
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確實值得讚揚物理定律的美,
01:09
but essentially what's happening here
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但是實際發生的是
01:11
-- (Laughter) --
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(笑聲)
01:13
is the energy from the sound via the air and gas molecules
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聲音的能量透過空氣和氣體分子
01:17
is influencing the combustion properties of propane,
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來影響丙烷的燃燒性質,
01:19
creating a visible waveform,
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因而產生一個可見的波形,
01:21
and we can see the alternating regions of compression
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而且我們能看到這些一下子壓縮
01:23
and rarefaction that we call frequency,
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又接著膨脹的變化區段,我們把它叫頻率,
01:25
and the height is showing us amplitude.
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而這個高度告訴我們的是振幅.
01:27
So let's change the frequency of the sound,
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好吧.那讓我們改變一下聲音的頻率,
01:29
and watch what happens to the fire.
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然後再看看火會發生什麽變化
01:31
(Higher frequency)
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(更高的頻率)
01:41
So every time we hit a resonant frequency we get a standing wave
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所以每當我們調到共鳴頻率時,會有駐波產生
01:44
and that emergent sine curve of fire.
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而那個像正弦函數的火焰就會出現.
01:46
So let's turn that off. We're indoors.
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好吧我們還是把這關了.我們在室內呢.
01:48
Thank you. (Applause)
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謝謝. (觀衆鼓掌)
01:53
I also have with me a flame table.
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我今天還帶來了一個火焰桌.
01:55
It's very similar to a Rubens' tube, and it's also used
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它跟魯本斯管挺像的,而且它還能用來
01:57
for visualizing the physical properties of sound,
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將聲音的物理性質圖像化,
01:59
such as eigenmodes, so let's fire it up
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比如說特徵模式,那我們把它點燃吧
02:01
and see what it does.
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然後看看會發生什麽.
02:07
Ooh. (Laughter)
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喔~(笑聲)
02:12
Okay. Now, while the table comes up to pressure,
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好吧.現在,當這個桌子受到到壓力,
02:14
let me note here that the sound is not traveling
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此時我注意到聲音(波形)不是以完美的直線在傳遞
02:16
in perfect lines. It's actually traveling in all directions,
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實際上是在各個方向傳遞,
02:19
and the Rubens' tube's a little like bisecting those waves
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而魯本斯管有點像是用一條線將這些波形分兩半
02:22
with a line, and the flame table's a little like
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而這個火焰桌有點像
02:24
bisecting those waves with a plane,
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用一個面將這些波分兩半,
02:26
and it can show a little more subtle complexity, which is why
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而它可以呈現一些微妙的複雜性,這就是爲啥
02:30
I like to use it to watch Geoff Farina play guitar.
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我喜歡用它去看Geoff Farina彈吉他.
02:32
(Music)
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(音樂)
03:15
All right, so it's a delicate dance.
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不錯,這是個曼妙的舞蹈.
03:16
If you watch closely — (Applause)
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如果你看的近一點--(觀衆鼓掌).
03:19
If you watch closely, you may have seen
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如果你仔細看,你可以發現
03:22
some of the eigenmodes, but also you may have seen
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一些特徵模式,不過你還可以發現
03:24
that jazz music is better with fire.
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爵士樂在火焰的陪襯下就感覺不錯.
03:29
Actually, a lot of things are better with fire in my world,
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實際上,我的世界裡,好多東西在火焰的陪襯下就不錯,
03:31
but the fire's just a foundation.
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不過火焰只不過是個陪襯.
03:33
It shows very well that eyes can hear,
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可以將耳朵能聽見的顯示得很清楚,
03:34
and this is interesting to me because
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我對這個很感興趣
03:36
technology allows us to present sound to the eyes
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因爲科技允許我們去用眼睛來感受聲音
03:39
in ways that accentuate the strength of the eyes
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從而加強我們眼睛接受聲音的敏銳度
03:41
for seeing sound, such as the removal of time.
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比如時間的轉移.
03:44
So here, I'm using a rendering algorithm to paint
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那麽這裏呢,我用透視演算法去畫出
03:47
the frequencies of the song "Smells Like Teen Spirit"
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歌曲"Smell Like Teen Spirit"的頻率
03:50
in a way that the eyes can take them in
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我們的眼睛因而可以將它們讀入
03:52
as a single visual impression, and the technique
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成爲一種獨一無二的直覺印象,這技術
03:54
will also show the strengths of the visual cortex
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也能印證視覺皮質對圖案辨認的能力
03:56
for pattern recognition.
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也能印證視覺皮質對圖案辨認的能力
03:58
So if I show you another song off this album,
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如果我給你這首專輯裏面另外一首歌,
04:00
and another, your eyes will easily pick out
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再另外一首,你的眼睛會輕易地捕捉到
04:03
the use of repetition by the band Nirvana,
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樂隊Nirvana(在音樂中)所使用的重複性,
04:06
and in the frequency distribution, the colors,
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以及在頻率分布,顔色方面,
04:08
you can see the clean-dirty-clean sound
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你可以發現這個一會兒清晰一會兒吵雜的聲音
04:11
that they are famous for,
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那種讓他們成名的音樂特色,
04:12
and here is the entire album as a single visual impression,
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這是個以獨特的直覺印象呈現的整張專輯,
04:16
and I think this impression is pretty powerful.
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我認爲這種印象十分的強大.
04:18
At least, it's powerful enough that
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至少,強大到
04:20
if I show you these four songs,
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如果我給你看四首歌,
04:21
and I remind you that this is "Smells Like Teen Spirit,"
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而且我提醒你這首是"Smells Like Teen Spirit",
04:24
you can probably correctly guess, without listening
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在不聽音樂的情況下,你可能會猜到這首歌,
04:26
to any music at all, that the song
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在不聽音樂的情況下,你可能會猜到這首歌,
04:27
a die hard Nirvana fan would enjoy is this song,
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Nirvana的死忠歌迷所喜愛的這首歌,
04:30
"I'll Stick Around" by the Foo Fighters,
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由Foo Fighters所製作的“I’will Stick Around”,
04:32
whose lead singer is Dave Grohl,
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他們的主唱是Dave Grohl,
04:34
who was the drummer in Nirvana.
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他是Nirvana的鼓手.
04:38
The songs are a little similar, but mostly
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這些歌曲都有點相似, 不過主要是
04:39
I'm just interested in the idea that someday maybe
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我覺得有一想法蠻有趣的,就是有一天我們買這首歌
04:41
we'll buy a song because we like the way it looks.
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是因爲我們喜歡它顯現的方式
04:45
All right, now for some more sound data.
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好吧, 再多呈現一點聲音數據,
04:46
This is data from a skate park,
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這是從滑冰公園所擷取的數據,
04:49
and this is Mabel Davis skate park
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而這是Mabel Davis滑冰公園
04:51
in Austin, Texas. (Skateboard sounds)
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在德州的奧斯丁.(滑板的響聲)
04:53
And the sounds you're hearing came from eight
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你聽到的聲音是從八個
04:54
microphones attached to obstacles around the park,
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在公園附近障礙上的麥克風擷取來的,
04:57
and it sounds like chaos, but actually
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聽起來有點混亂,不過實際上
04:59
all the tricks start with a very distinct slap,
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所有的特技從一個明顯拍擊聲開始,
05:02
but successful tricks end with a pop,
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不過成功的特技最後會砰一聲結束,
05:04
whereas unsuccessful tricks
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而沒表演好的特技
05:05
more of a scratch and a tumble,
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還會摻雜更多的刮傷和翻滾的聲音,
05:07
and tricks on the rail will ring out like a gong, and
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而在欄杆上的特技會發出一個像是敲鑼的聲音,
05:11
voices occupy very unique frequencies in the skate park.
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而這些聲音在這個公園都有著獨特的頻率,
05:14
So if we were to render these sounds visually,
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所以,我們要是想把這些聲音圖像化,
05:16
we might end up with something like this.
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我們應該要得到像這樣的東西.
05:17
This is all 40 minutes of the recording,
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這是40分鐘的記錄,
05:20
and right away the algorithm tells us
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從這演算法我們立即發現
05:22
a lot more tricks are missed than are made,
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沒做成功的特技比成功的特技還要多,
05:24
and also a trick on the rails is a lot more likely
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而且在這些欄杆上的特技很有可能會
05:26
to produce a cheer, and if you look really closely,
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帶來更多的歡呼聲,如果你非常仔細看的話,
05:29
we can tease out traffic patterns.
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我們可以找出關於(滑冰公園內)流量的圖案.
05:31
You see the skaters often trick in this direction. The obstacles are easier.
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你會看到溜冰的人通常朝這個方向,(這方向的)障礙比較少.
05:37
And in the middle of the recording, the mics pick this up,
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然後在這個記錄的中央, 麥克風把這個記錄下來,
05:39
but later in the recording, this kid shows up,
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但是在這記錄的後面,這個小孩出現,
05:42
and he starts using a line at the top of the park
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他在公園最高處沿著一條新的路線開始溜冰
05:45
to do some very advanced tricks on something
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做一些難度高的特技
05:46
called the tall rail.
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稱作高欄特技.
05:47
And it's fascinating. At this moment in time,
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而這相當有看頭.在這個時候,
05:49
all the rest of the skaters turn their lines 90 degrees
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其餘所有溜冰的人都把他們的路線轉了90度讓路給他.
05:53
to stay out of his way.
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其餘所有溜冰的人都把他們的路線轉了90度讓路給他.
05:55
You see, there's a subtle etiquette in the skate park,
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你可以看到,在這個公園裡有個約定俗成的禮儀
05:57
and it's led by key influencers,
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是由頗具影響力的人主導的,
05:59
and they tend to be the kids who can do the best tricks,
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而他們傾向是作高難度動作的小孩,
06:02
or wear red pants, and on this day the mics picked that up.
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或者是穿紅褲子的,而這天麥克風就記錄下這現象.
06:04
All right, from skate physics to theoretical physics.
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好吧,從溜冰物理到理論物理.
06:08
I'm a big fan of Stephen Hawking,
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我是Stephen Hawking的大粉絲,
06:10
and I wanted to use all eight hours
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我想用他在劍橋八個小時的講座來表示我對他的敬意
06:11
of his Cambridge lecture series to create an homage.
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我想用他在劍橋八個小時的講座來表示我對他的敬意.
06:14
Now, in this series he's speaking with the aid of a computer,
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現在呢,在這堂講座裡,他借助於電腦作演講,
06:17
which actually makes identifying the ends of sentences
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這樣確實比較容易分辨句子是否結束
06:20
fairly easy. So I wrote a steering algorithm.
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因此我寫了個操縱算法.
06:23
It listens to the lecture, and then it uses
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它一邊聽講座,然後一邊利用
06:25
the amplitude of each word to move a point on the x-axis,
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每個詞的振幅在x軸方向上來回移動點,
06:28
and it uses the inflection of sentences
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它還利用句子的音調變化
06:31
to move a same point up and down on the y-axis.
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針對同一點在Y軸方向上下移動.
06:33
And these trend lines, you can see, there's more questions
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然後這些指明趨勢的線,你可以看到在物理世界中
06:36
than answers in the laws of physics,
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未知比已知多,
06:38
and when we reach the end of a sentence,
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每當我們聽完一個句子,
06:40
we place a star at that location.
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我們就在(那個句子對應到的)那個地方放一顆星星.
06:42
So there's a lot of sentences, so a lot of stars,
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所以呢很多句子就產生很多星星,
06:45
and after rendering all of the audio, this is what we get.
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播完所有的語音檔後,我們就得到了這個
06:47
This is Stephen Hawking's universe.
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這就是Stephen Hawking的宇宙.
06:50
(Applause)
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(觀眾鼓掌)
06:57
It's all eight hours of the Cambridge lecture series
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全部是在劍橋的八個小時的講座
06:59
taken in as a single visual impression,
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以一個獨一無二的直覺印象呈現,
07:01
and I really like this image,
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我相當喜歡這個圖案.
07:03
but a lot of people think it's fake.
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不過很多人認為它是假的.
07:05
So I made a more interactive version,
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所以我做了個互動版本,
07:07
and the way I did that is I used their position in time
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而且我所使用的方式是利用他們在時間軸上出現的位置
07:13
in the lecture to place these stars into 3D space,
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將這些星星放置在3D空間裡(對應位置),
07:15
and with some custom software and a Kinect,
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同時利用一些客製化軟體和一個Kinect,
07:17
I can walk right into the lecture.
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這樣我就能”走進”課堂中.
07:20
I'm going to wave through the Kinect here
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我要握著這個Kinect 作揮手動作
07:22
and take control, and now I'm going to reach out
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然後作一些操控,接著我伸手去
07:24
and I'm going to touch a star, and when I do,
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抓一顆星星,當我這樣做的時候,
07:27
it will play the sentence
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它會播出(這個星星所對應到的)這句話.
07:29
that generated that star.
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它會播出(這個星星所對應到的)這句話.
07:30
Stephen Hawking: There is one, and only one, arrangement
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Stephen Hawking:這裡有一個,獨一無二的(星星位置)分布
07:34
in which the pieces make a complete picture.
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(星星所在的)各個位置構成一個完整的圖案.
07:37
Jared Ficklin: Thank you. (Applause)
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Jared Ficklin:謝謝 (觀眾鼓掌)
07:41
There are 1,400 stars.
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這裡面一共有1400顆星星
07:44
It's a really fun way to explore the lecture,
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這是個很有意思的方式去探索這個講座,
07:46
and, I hope, a fitting homage.
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我希望(這是表示)合適敬意的方式.
07:47
All right. Let me close with a work in progress.
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好的.讓我們以接下來的作品來結束今天的演講.
07:53
I think, after 30 years, the opportunity exists
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我認為,30年後,我們有可能
07:56
to create an enhanced version of closed captioning.
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去創造沒字幕的特殊版本.
07:58
Now, we've all seen a lot of TEDTalks online,
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現在,我們在網上可以看到好多TED演講,
08:00
so let's watch one now with the sound turned off
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因此呢讓我們將聲音關掉去看一個吧
08:03
and the closed captioning turned on.
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當然我們把字幕打開
08:07
There's no closed captioning for the TED theme song,
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TED片頭曲是沒有字幕,
08:09
and we're missing it, but if you've watched enough of these,
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因此我們經常錯過這部分,不過你已經看得夠多了,
08:11
you hear it in your mind's ear,
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你可以在你心裡聽到這片頭曲,
08:13
and then applause starts.
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接著呢開始聽到掌聲.
08:16
It usually begins here, and it grows and then it falls.
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通常(掌聲)是這樣開始,先漸強,最後漸弱.
08:18
Sometimes you get a little star applause,
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但有時候你僅會有一點的掌聲,
08:20
and then I think even Bill Gates takes a nervous breath,
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而且我認為即使Bill Gates也緊張地深吸一口氣,
08:22
and the talk begins.
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然後開始演講.
08:24
All right, so let's watch this clip again.
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好吧,那麼就讓我們再看一次這個片段.
08:30
This time, I'm not going to talk at all.
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這次,我不準備說話了.
08:31
There's still going to be no audio,
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依然是沒有聲音,
08:32
but what I am going to do is I'm going to render the sound
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不過這回我要做的就是讓這個聲音圖像化,
並顯示在銀幕的最底下
08:34
visually in real time at the bottom of the screen.
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不過這回我要做的就是讓這個聲音圖像化,
並顯示在銀幕的最底下
08:38
So watch closely and see what your eyes can hear.
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所以呢 更靠近一點看,看看你的眼睛能”聽”到什麼.
09:03
This is fairly amazing to me.
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這個對我來說非常神奇
09:05
Even on the first view, your eyes will successfully
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即使看第一次,你的眼睛也會成功的
09:08
pick out patterns, but on repeated views,
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擷取一些圖案,不過在重複看之後,
09:11
your brain actually gets better
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你的腦子將圖案轉化為信息能力方面會變得更好
09:13
at turning these patterns into information.
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你的腦子將圖案轉化為信息能力方面會變得更好
09:14
You can get the tone and the timbre
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你可以感覺到說話人的語氣和音色
09:16
and the pace of the speech,
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以及演講的速度,
09:17
things that you can't get out of closed captioning.
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這些是你從字幕中得不到的東西.
09:19
That famous scene in horror movies
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恐怖電影中的經典畫面
09:21
where someone is walking up from behind
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也就是當有人從後面走來時
09:24
is something you can see,
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變成了你可以看到的東西,
09:26
and I believe this information would be something
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因此我相信這個東西會成為
09:29
that is useful at times when the audio is turned off
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當聲音被關掉的時候的一個有用的工具
09:31
or not heard at all, and I speculate that deaf audiences
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或者根本無法聽到的時候,我還認為耳聾的觀眾
09:34
might actually even be better
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會比看正常的聽眾更擅長看聲音
09:36
at seeing sound than hearing audiences.
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會比看正常的聽眾更擅長看聲音
09:37
I don't know. It's a theory right now.
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我也不太清楚.目前為這只是個理論.
09:39
Actually, it's all just an idea.
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實際上,這只不過是個想法.
09:40
And let me end by saying that sound moves in all directions,
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我結束前我說這樣一句話吧:聲音會向所有的方向移動,
09:45
and so do ideas.
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想法也會。
09:47
Thank you. (Applause)
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