Massive-scale online collaboration | Luis von Ahn

Translator: Bruce Ding Reviewer: Yuping Huang

How many of you had to fill out a web form

有幾多人填寫網頁表格時

where you've been asked to read

a distorted sequence of characters like this?

需要識別變形驗證碼？

How many of you found it really annoying?

有幾多人覺得哩樣嘢真係好煩？

(Laughter)

都唔少啊。哩樣嘢就係我發明嘅

OK, outstanding. So I invented that.

(Laughter)

（笑聲）

或者講我係發明嘅其中一個

Or I was one of the people who did it.

That thing is called a CAPTCHA.

哩樣嘢叫 CAPTCHA

佢之所以會出現喺網頁度

And it is there to make sure you, the entity filling out the form,

係因為電腦要確認你、填格嘅 哩個人係一個人類

are a human and not a computer program

而唔係電腦程式 為咗千萬次重複填表嘅電腦程式

that was written to submit the form millions of times.

The reason it works is because humans, at least non-visually-impaired humans,

至所以有變形驗證碼

係因為正常人讀哩啲扭曲文字 完全冇難度

have no trouble reading these distorted characters,

whereas programs can't do it as well yet.

但電腦就仲未做到

In the case of Ticketmaster,

譬如，喺 Ticketmaster 網站上

the reason you have to type these characters

你要輸入哩啲變形驗證碼嘅原因

is to prevent scalpers from writing a program

係為咗防止黃牛用程式

that can buy millions of tickets, two at a time.

每次兩張咁買成幾萬張飛

CAPTCHAs are used all over the Internet.

驗證碼喺網絡十分普遍

And since they're used so often,

既然我哋咁頻繁用到佢

a lot of times the sequence of random characters shown to the user

於是好多時候用戶遇到一啲問題

is not so fortunate.

So this is an example from the Yahoo registration page.

哩度係一個來自雅虎註冊頁嘅例子

The random characters that happened to be shown to the user

展示畀用戶嘅隨機字符「WAIT」 咁啱可以組成一個英文字「等待」

were W, A, I, T, which, of course, spell a word.

最有趣嘅係

But the best part is the message

20 分鐘後雅虎網上支援組收到訊息

that the Yahoo help desk got about 20 minutes later.

[Help! I've been waiting for over 20 minutes and nothing happens.]

（文字：幫我啊！ 我都等咗廿幾分鐘，畫面依然冇郁）

(Laughter)

（笑聲）

This person thought they needed to wait.

佢仲以為網站叫佢等

This, of course, is not as bad as this poor person.

當然冇嘢比哩個人幾騎

(Laughter)

（笑聲）

CAPTCHA Project is something that we did at Carnegie Melllon over 10 years ago,

驗證碼計劃係我哋十多年前 喺卡內基梅隆大學搞起嘅

之後開始被廣泛應用

and it's been used everywhere.

Let me now tell you about a project that we did a few years later,

宜家等我來講下我哋幾年後 搞嘅另一個項目

即係驗證碼嘅進化版

which is sort of the next evolution of CAPTCHA.

我哋稱之為「reCAPTCHA」

This is a project that we call reCAPTCHA,

哩個項目最先喺卡內基梅隆大學開始

which is something that we started here at Carnegie Mellon,

之後仲成為一間公司

then we turned it into a start-up company.

大概一年半之前

And then about a year and a half ago, Google actually acquired this company.

谷歌收購埋哩間公司

宜家等我來講講哩個項目係點開始嘅

Let me tell you what this project started.

This project started from the following realization:

哩個項目出於以下嘅事實：

全球每日輸入大概 2 億次驗證碼

It turns out that approximately 200 million CAPTCHAs

are typed everyday by people around the world.

When I first heard this, I was quite proud of myself.

我第一次聽到嘅時候都幾自豪

我諗，我哋嘅研究都幾大影響喔

I thought, look at the impact my research has had.

跟住我就覺得唔對路

But then I started feeling bad.

因為你每輸入一次驗證碼

Here's the thing: each time you type a CAPTCHA,

你就浪費咗 10 秒鐘嘅時間

essentially, you waste 10 seconds of your time.

And if you multiply that by 200 million,

如果你將佢乘以 2 億

you get that humanity is wasting about 500,000 hours every day

咁人類因為輸入驗證碼

而每日浪費咗 50 萬個小時

typing these annoying CAPTCHAs.

(Laughter)

所以我就開始覺得唔爽

So then I started feeling bad.

(Laughter)

（笑聲）

And then I started thinking, of course, we can't just get rid of CAPTCHAs,

跟住我就開始諗

嗯，當然啦 我哋冇可能放棄驗證碼糸統㗎嘛

因為網絡安全旨意佢

because the security of the web depends on them.

但係咪有辦法可以利用佢 來為人類做啲好事？

But then I started thinking, can we use this effort

for something that is good for humanity?

So see, here's the thing.

嗯，關鍵在於

While you're typing a CAPTCHA, during those 10 seconds,

當你輸入一個驗證碼嘅時候 喺嗰 10 秒鐘

你嘅大腦係度做緊一啲好神奇嘅 而電腦未做到嘅嘢

your brain is doing something amazing.

Your brain is doing something that computers cannot yet do.

So can we get you to do useful work for those 10 seconds?

我哋可唔可以用哩 10 秒 做啲有用嘅嘢呢？

Is there some humongous problem that we cannot yet get computers to solve,

換個講法

係唔係有啲計算機無法解決嘅龐大問題

yet we can split into tiny 10-second chunks

而我哋可以將佢分為 10 個 10 秒嘅子問題呢？

such that each time somebody solves a CAPTCHA,

咁樣，每次有人輸入一個驗證碼嘅時候

they solve a little bit of this problem?

佢哋就解決咗哩個問題嘅其中一部分

答案係肯定嘅 而哩個就係我哋做緊嘅嘢

And the answer to that is "yes," and this is what we're doing now.

你可能唔知道 宜家你每次輸入驗證碼嘅時候

Nowadays, while you're typing a CAPTCHA,

你唔單止證明咗自己人類嘅身份

not only are you authenticating yourself as a human,

同時亦喺度幫緊我哋數碼化圖書

but in addition you're helping us to digitize books.

等我來解釋一下：

Let me explain how this works.

There's a lot of projects trying to digitize books.

目前已經有好多項目做緊圖書數碼化

Google has one. The Internet Archive has one.

谷歌有一個

「互聯網檔案計劃」都有一個

亞馬遜同埋 Kindle 亦都試緊數碼化圖書

Amazon, with the Kindle, is trying to digitize books.

基本上，數碼化圖書要由一本舊書開始

Basically, the way this works is you start with an old book.

You've seen those things, right?

你睇過書㗎吓？ 一本書？

Like a book?

（笑聲）

(Laughter)

So you start with a book and then you scan it.

你從一本實體書開始，掃描佢每一頁

Now, scanning a book

掃描一本書 就好似對本書每一頁影一張相

is like taking a digital photograph of every page.

畀到你每一頁嘅樣貌

It gives you an image for every page.

哩啲影像包括咗書每一頁嘅文字

This is an image with text for every page of the book.

The next step in the process is that the computer needs to be able

下一步就係電腦需要認到 哩個影像入邊嘅所有文字

to decipher the words in this image.

目前使用嘅技術叫做 OCR

That's using a technology called OCR, for optical character recognition,

即係「光學字符識別」

which takes a picture of text

OCR 首先獲取文字嘅影像

and tries to figure out what text is in there.

然後嘗試辨認出 出現喺嗰個影像入邊嘅文字

Now, the problem is that OCR is not perfect.

問題在於 OCR 並唔完美

Especially for older books

尤其用喺古書嘅時候

where the ink has faded and the pages have turned yellow,

古書上面嘅墨跡已經變淡

紙質開始變黃

OCR cannot recognize a lot of the words.

好多文字 OCR 認唔到

For things that were written more than 50 years ago,

譬如，五十幾年前嘅書

當中大概有 30% 嘅文字 唔可以俾電腦識別

the computer cannot recognize about 30 percent of the words.

所以，我哋喺度做緊嘅嘢

So now we're taking all of the words that the computer cannot recognize

就係將所有哩啲電腦認唔到嘅文字 攞出來

and we're getting people to read them for us

等人喺網上輸入驗證碼嘅同時 幫我哋認啲字

while they're typing a CAPTCHA on the Internet.

所以，下一次你輸入驗證碼嘅時候

So the next time you type a CAPTCHA, these words that you're typing

你輸入嘅嗰啲文字實質上 來自被數碼化緊嘅圖書

are actually words from books that are being digitized

that the computer could not recognize.

而所有哩些文字都係電腦認唔到嘅

The reason we have two words nowadays instead of one

另外，宜家之所以出現兩組文字 而唔係一組文字

is because one of the words

係因為其中一組文字

is a word that the system just got out of a book,

係系統喺書入邊認唔到嘅字

it didn't know what it was and it's going to present it to you.

但係既然佢唔知答案係乜嘢 佢都唔可以判斷你認得啱唔啱

But since it doesn't know the answer, it cannot grade it.

所以我哋嘅做法就係 畀一組系統已知嘅文字組合你

So we give you another word,

for which the system does know the answer.

We don't tell you which one's which and we say, please type both.

我哋唔講畀你知邊個打邊個

我哋淨係講「請將兩個組合輸入」

And if you type the correct word

如果你正確輸入電腦已知嘅組合

for the one for which the system knows the answer,

電腦就認為你係人類

it assumes you are human

and it also gets some confidence that you typed the other word correctly.

同時對你輸入嘅另一個組合多幾分信心

如果我哋對 10 個人重複哩個過程

And if we repeat this process to 10 different people

而佢哋都輸入咗個新詞係乜嘢

and they agree on what the new word is,

咁我哋就可以正確咁數碼化多一個詞語

then we get one more word digitized accurately.

哩樣就係系統嘅運作原理

So this is how the system works.

同時，因為我哋已經喺三四年前 發佈咗哩個系統

And since we released it about three or four years ago,

好多網站已經由以前嘥用戶時間嘅 舊驗證碼系統

a lot of websites have started switching from the old CAPTCHA,

where people wasted their time,

轉去哩個新嘅 可以幫助數碼化圖書嘅系統

to the new CAPTCHA where people are helping to digitize books.

例如，喺 Ticketmaster 嘅網站上

So every time you buy tickets on Ticketmaster,

你每一次買飛，都係幫緊數碼化圖書

you help to digitize a book.

喺臉書，你每一次加好友或者打招呼

Facebook: Every time you add a friend or poke somebody,

你都係幫緊數碼化圖書

you help to digitize a book.

推特同埋另外 35 萬個網站 都用緊 reCAPTCHA

Twitter and about 350,000 other sites are all using reCAPTCHA.

事實上，使用 reCAPTCHA 嘅 網站數量如此之多

And the number of sites that are using reCAPTCHA is so high

以至到我哋每日數碼化嘅文字數量 亦都十分之高

that the number of words we're digitizing per day is really large.

大概有 1,000 萬之多

It's about 100 million a day,

which is the equivalent of about two and a half million books a year.

相當於每年數碼化咗 250 萬本書

And this is all being done one word at a time

而哩一切都係一個字一個字咁

by just people typing CAPTCHAs on the Internet.

由用戶喺網上輸入驗證碼得來嘅

(Applause)

（鼓掌）

Now, of course,

當然

since we're doing so many words per day,

既然我哋每日都可以完成咁多字

funny things can happen.

有趣嘅事就有可能會發生

This is especially true because now we're giving people

尤其而家，我哋同時向用戶展示 兩個隨機產生、並列出現嘅英文單詞

two randomly chosen English words next to each other.

So funny things can happen.

好笑嘅嘢會發生

For example, we presented this word.

譬如，我哋展示咗哩個詞語

詞語「基督徒」冇乜問題

It's the word "Christians"; there's nothing wrong with it.

But if you present it along with another randomly chosen word,

但係如果你同另外一個隨機選嘅詞語 擺埋一齊

就可能搞禍咗

bad things can happen.

我哋就見到咁樣嘅組合 （英文意思：壞基督徒）

So we get this.

[bad Christians]

但更衰嘅係

But it's even worse, because the website where we showed this

哩组文字咁啱出現喺一個叫 「上帝王國嘅使館」嘅網站上

actually happened to be called The Embassy of the Kingdom of God.

（笑聲）

(Laughter)

Oops.

哎呀

(Laughter)

（笑聲）

哩度仲有一個

Here's another really bad one.

JohnEdwards.com

JohnEdwards.com

[Damn liberal]

（譯：可惡嘅自由派）

(Laughter)

（笑聲）

所以我哋每日都喺度侮辱人

So we keep on insulting people left and right everyday.

當然，我哋不單止侮辱人

Of course, we're not just insulting people.

既然我哋隨機產生兩組字

Here's the thing. Since we're presenting two randomly chosen words,

有趣嘅嘢可能會發生

interesting things can happen.

So this actually has given rise to a really big Internet meme

所以佢實際上催生咗

一個十分龐大 有成千上萬人參與嘅互聯網潮流

that tens of thousands of people have participated in,

叫「驗證碼嘅藝術」

which is called CAPTCHA art.

I'm sure some of you have heard about it.

我相信你哋在座一啲人已經聽過

Here's how it works.

佢係咁運作嘅

Imagine you're using the Internet and you see a CAPTCHA

想像你自己正喺度用緊互聯網

如果你見到一個有啲奇怪嘅驗證碼

that you think is somewhat peculiar,

like this CAPTCHA.

好似咁 （譯：隱形嘅土司機）

[invisible toaster]

What you're supposed to do is you take a screenshot of it.

然後，你應該做嘅係將佢截圖落來

跟住，當然啦，你將個驗證碼填好

Then of course, you fill out the CAPTCHA because you help us digitize a book.

因為咁樣已經幫緊我哋數碼化圖書

所以，你首先截圖落來

But first you take a screenshot

and then you draw something that is related to it.

然後畫一啲同佢相關嘅嘢

（笑聲）

(Laughter)

That's how it works.

就係咁

(Laughter)

There are tens of thousands of these.

哩度有成千上萬咁樣嘅作品

Some of them are very cute.

有啲都好可愛咖 （譯：捉緊佢）

[clenched it]

（笑聲）

(Laughter)

Some of them are funnier.

有啲更加搞笑

[stoned Founders]

（譯：飲大咗嘅建國者）

(Laughter)

（笑聲）

And some of them, like paleontological shvisle ...

仲有一啲

譬如「古生物學嘅史維錘」

(Laughter)

佢哋包括饒舌家 Snoop Dogg

they contain Snoop Dogg.

(Laughter)

（笑聲）

OK, so this is my favorite number of reCAPTCHA.

哩個係我最鐘意嘅 reCAPTCHA 數字

So this is the favorite thing that I like about this whole project.

我最鐘意嘅部分

7 億 5 千萬哩個數字

This is the number of distinct people

係通過 reCAPTCHA 幫我哋 數碼化圖書嘅人數

that have helped us digitize at least one word out of a book through reCAPTCHA:

750 million, a little over 10 percent of the world's population,

剛好世界超過百分之一嘅人口 已經幫過我哋數碼化人類知識

has helped us digitize human knowledge.

And it is numbers like these that motivate my research agenda.

就係哩個數字激勵我去研究一個問題：

So the question that motivates my research is the following:

If you look at humanity's large-scale achievements,

如果你睇睇人類嘅大型成就

these really big things

嗰啲歷史上人類合力完成嘅大事

that humanity has gotten together and done historically --

like, for example, building the pyramids of Egypt

譬如，建造埃及金字塔

or the Panama Canal

或者巴拿馬運河

or putting a man on the Moon --

或者將人類送上月球

there is a curious fact about them,

哩度有一個幾有趣嘅 關於呢啲大事嘅事實

and it is that they were all done with about the same number of people.

就係佢哋全部都係 由差唔多數量嘅人完成嘅

It's weird; they were all done with about 100,000 people.

好奇怪，佢哋全部都係 由差唔多 10 萬人完成嘅

And the reason for that is because, before the Internet,

原因係，喺互聯網出現之前

集合超過 10 萬人 ——唔好講話畀錢佢哋

coordinating more than 100,000 people,

let alone paying them, was essentially impossible.

係幾乎冇可能嘅

但係因為有咗互聯網

But now with the Internet, I've just shown you a project

我啱啱展示畀你哋嘅項目 就有 7 億 5 千萬人參與

where we've gotten 750 million people to help us digitize human knowledge.

來幫我哋數碼化人類知識

So the question that motivates my research is,

所以激勵我研究嘅問題就係

if we can put a man on the Moon with 100,000,

如果我哋可以用 10萬人 將人類送上月球

what can we do with 100 million?

我哋可以用 1億人做啲乜嘢？

So based on this question,

基於哩個問題

we've had a lot of different projects that we've been working on.

我哋開展咗好多唔同嘅項目

等我同你哋介紹下我最為之興奮嘅一個

Let me tell you about one that I'm most excited about.

This is something that we've been semiquietly working on

哩個項目我哋已經半公開地 進行咗差唔多一年半

for the last year and a half or so.

佢仲未正式運行，叫做 Duolingo

It hasn't yet been launched. It's called Duolingo.

Since it hasn't been launched, shhh!

因為我哋仲未投入使用，所以，噓！

(Laughter)

（笑聲）

Yeah, I can trust you'll do that.

我相信你哋都會守口如瓶嘅

So this is the project. Here's how it started.

哩個項目係咁樣開始嘅

It started with me posing a question to my graduate student, Severin Hacker.

我向我嘅研究生 Severin Hacker 提出一個問題

OK, that's Severin Hacker.

——哩個就係佢

我向佢提咗一個問題

So I posed the question to my graduate student.

By the way, you did hear me correctly; his last name is Hacker.

——順便一提，你冇聽錯

佢確實姓「Hacker（譯︰駭客）」

(Laughter)

So I posed this question to him: How can we get 100 million people

我向佢提出咗哩個問題：

我哋點樣先可以叫 1 億人義務咁

translating the web into every major language for free?

幫手將互聯網翻譯成主要嘅語言？

There's a lot of things to say about this question.

嗯，關於哩個題目我哋有好多嘢可以講

First of all, translating the web.

首先係翻譯網頁

Right now, the web is partitioned into multiple languages.

互聯網分為多種語言

其中一大部分係英文

A large fraction of it is in English.

如果你唔識英文 你就冇辦法接觸到互聯網

If you don't know English, you can't access it.

但同時亦有一大部分係其他語言

But there's large fractions in other different languages,

同樣，如果你唔識嗰啲語言 你亦無法接觸到互聯網

and if you don't know them, you can't access it.

所以我好想可以將整個互聯網 或者至少係大部分

So I would like to translate all of the web,

or at least most of it, into every major language.

翻譯成每一種主要語言

哩個就係我想做嘅事

That's what I would like to do.

Now, some of you may say, why can't we use computers to translate?

但有啲人可能會問 點解唔用電腦來翻譯呢？

Machine translation is starting to translate

既然機器翻譯已經開始出現

some sentences here and there.

Why can't we use it to translate the web?

點解我哋唔用佢翻譯整個互聯網呢？

The problem with that is it's not yet good enough

唔， 問題在於，機器翻譯仲未夠成熟

而且哩個問題喺未來 15、20 年 亦唔一定解決到

and it probably won't be for the next 15 to 20 years.

機器翻譯出錯太多

It makes a lot of mistakes. Even when it doesn't,

即使佢冇出錯

since it makes so many mistakes, you don't know whether to trust it or not.

但因為佢出錯太多 你好難講應唔應該信佢

舉一個機器翻譯嘅例子

So let me show you an example

of something that was translated with a machine.

哩個係一篇網上論壇嘅帖文

Actually, it was a forum post.

It was somebody who was trying to ask a question about JavaScript.

由一位網民發表 問一個關於 Java 語言嘅問題

It was translated from Japanese into English.

帖文由日文譯成英文

So I'll just let you read.

你可以睇

This person starts apologizing

哩個人首先為使用電腦翻譯而道歉

for the fact that it's translated with a computer.

So the next sentence is going to be the preamble to the question.

下一個句子開始

佢喺度解釋緊一啲嘢

So he's just explaining something.

請留意，哩個係一個 關於 Java 語言嘅問題

Remember, it's a question about JavaScript.

[At often, the goat-time install a error is vomit.]

（譯：常常，山羊時間安裝 一個錯誤係嘔吐）

(Laughter)

（笑聲）

Then comes the first part of the question.

跟著係哩個問題嘅第一個部分

[How many times like the wind, a pole, and the dragon?]

（譯：有幾多次好似風、柱、龍？）

(Laughter)

（笑聲）

跟住係我最鐘意嘅部分

Then comes my favorite part of the question.

[This insult to father's stones?]

（譯：哩個對父親嘅侮辱？）

(Laughter)

（笑聲）

跟著到咗問題嘅最後部分 成件事我最鐘意嘅部分

And then comes the ending,

which is my favorite part of the whole thing.

（文字：請為你嘅愚蠢道歉。

[Please apologize for your stupidity. There are a many thank you.]

哩度有對你嘅好多感謝。）

(Laughter)

（笑聲）

OK, so computer translation, not yet good enough.

所以，電腦翻譯未成熟

So back to the question.

返返去問題

我哋需要人來翻譯互聯網

So we need people to translate the whole web.

你下一個要問嘅問題可能係

So now the next question you may have is,

點解我哋唔使錢叫人來做呢？

well, why can't we just pay people to do this?

我哋可以使錢請專業嘅翻譯家 來翻譯成個互聯網

We could pay professional translators to translate the whole web.

我哋可以咁做

We could do that.

Unfortunately, it would be extremely expensive.

但不幸嘅係，咁樣可能會非常貴

For example, translating a tiny fraction of the whole web, Wikipedia,

例如，將互聯網中嘅極小極小嘅一部分 即係維基百科

into one other language, Spanish.

翻譯成西班牙文

OK? Wikipedia exists in Spanish,

雖然有西班牙文嘅維基百科

but it's very small compared to the size of English.

但相比於英文維基百科，佢嘅內容好少

大概只有英文維基百科嘅 20%

It's about 20 percent of the size of English.

如果我哋想將另外嗰 80% 翻譯為西班牙文

If we wanted to translate the other 80 percent into Spanish,

可能要使五千萬美元

it would cost at least 50 million dollars --

即使係最平嘅服務外包國家

and this is even at the most exploited, outsourcing country out there.

So it would be very expensive.

翻譯費用都會好貴

So what we want to do is, we want to get 100 million people

我哋想做嘅係將 1 億人聯合起來 將互聯網翻譯為任何一種主要語言

translating the web into every major language for free.

而唔使一分一毫

如果哩個係你想做嘅

If this is what you want to do, you quickly realize

你好快就會發現 自己會面臨兩個幾大嘅難題

you're going to run into two big hurdles, two big obstacles.

The first one is a lack of bilinguals.

第一個就係缺少雙語人才

So I don't even know

我甚至唔知道

if there exists 100 million people out there using the web

係唔係有 1 億擁有足夠雙語能力嘅人 會幫我哋翻譯

who are bilingual enough to help us translate.

哩個係個大問題

That's a big problem.

The other problem you're going to run into is a lack of motivation.

另一個你會遇到嘅問題係缺少鼓勵

我哋點樣鼓勵人哋義務翻譯網頁呢？

How are we going to motivate people to actually translate the web for free?

通常來講，你必須使錢請人來做哩啲

Normally, you have to pay people to do this.

So how are we going to motivate them to do it for free?

點樣能夠鼓勵人哋義務來翻譯呢？

當我哋開始諗哩啲問題嘅時候 我哋就俾哩兩個難題限住

When we were starting to think about this, we were blocked by these two things.

但後來我哋發現係有辦法嘅

But then we realized, there's a way

to solve both these problems with the same solution.

有一個一石二鳥嘅辦法

To kill two birds with one stone.

就係將翻譯語言轉變為大家都想做嘅事

And that is to transform language translation

into something that millions of people want to do

and that also helps with the problem of lack of bilinguals,

同時又消除冇雙語人才嘅問題

and that is language education.

嗰樣就係語言教育啦

So it turns out that today,

實際上，現時有超過 12 億人學緊外語

there are over 1.2 billion people learning a foreign language.

People really want to learn a foreign language.

大家都好想學外語

And it's not just because they're being forced to do so in school.

但唔係單單因為學校被逼咁做

因為喺美國

In the US alone, there are over five million people

有超過 500 萬人喺軟件上 花費咗超過 500 美元學習一種新語言

who have paid over $500 for software to learn a new language.

所以，大家真係好想學新語言

So people really want to learn a new language.

So what we've been working on for the last year and a half

我哋喺過去一年半籌建嘅一個網站

叫 Duolingo

is a new website -- it's called Duolingo --

Duolingo 嘅基本理念係 人哋可以免費學習一種新語言

where the basic idea is people learn a new language for free

while simultaneously translating the web.

同時義務翻譯網頁

簡單來講，佢哋喺度通過實踐來學習

And so basically, they're learning by doing.

So the way this works

Duolingo 運作嘅方式係

is whenever you're a just a beginner, we give you very simple sentences.

如果你係初學者 我哋會畀非常非常簡單嘅句子你

There's a lot of very simple sentences on the web.

當然網上有好多簡單嘅句子

We give you very simple sentences along with what each word means.

我哋畀你非常非常簡單嘅句子 同每個詞語嘅意思

And as you translate them

隨著你翻譯佢哋 加上睇其他人點樣翻譯佢哋

and as you see how other people translate them,

你就會開始學習嗰種語言

you start learning the language.

當你變得越來越進階嘅時候

And as you get more advanced,

we give you more complex sentences to translate.

我哋就會畀你更加複雜句子翻譯

But at all times, you're learning by doing.

無論幾時，你都係通過練習來學習

Now, the crazy thing about this method is that it actually really works.

哩種方法瘋狂在於佢真係會成功

People are really learning a language.

首先，啲人真係學緊語言

We're mostly done building it and now we're testing it.

我哋已經整好個網站，宜家喺度測試

人哋真係可以用佢來學習語言

People really can learn a language with it.

And they learn it about as well as the leading language learning software.

學出來亦可以同其他領先嘅 語言學習軟件學出來一樣咁好

So people really do learn a language.

人哋真係可以學一門語言

唔單止學得一樣好

And not only do they learn it as well, but actually it's more interesting.

佢實際上亦更加有趣

因為喺 Duolingo 啲人用現實材料來學

Because with Duolingo, people are learning with real content.

相對於用教材寫嘅句子 人哋學緊真實嘅內容

As opposed to learning with made-up sentences,

people are learning with real content, which is inherently interesting.

從本質上就有趣好多

人哋真係學習一種語言

So people really do learn a language.

But perhaps more surprisingly,

可能更令人驚奇嘅係

the translations that we get from people using the site,

用緊哩個網站嘅人 ——即使佢哋只係初學者

even though they're just beginners,

the translations that we get

所寫嘅翻譯同嗰啲專業嘅翻譯家 竟然一樣準確

are as accurate as those of professional language translators,

which is very surprising.

等我舉個例子

So let me show you one example.

This is a sentence that was translated from German into English.

哩個係一個從德文翻譯成英文嘅句子

上面係德文

The top is the German. The middle is an English translation

中間係由專業譯者做嘅英文翻譯

that was done by a professional translator

who we paid 20 cents a word for this translation.

我哋為哩個翻譯嘅每個字使咗 20 美仙

And the bottom is a translation by users of Duolingo,

最下面嘅翻譯係由之前完全唔識德文嘅

none of whom knew any German before they started using the site.

我哋網站嘅用戶做嘅翻譯

If you can see, it's pretty much perfect.

你哋可以見到，哩個翻譯係幾完美嘅

Of course, we play a trick here

當然，我哋用咗一啲方法 令哩個翻譯同專業翻譯一樣咁好

to make the translations as good as professional language translators.

我哋集合多個用戶嘅翻譯

We combine the translations of multiple beginners

來得到一個專業譯者水準嘅翻譯

to get the quality of a single professional translator.

Now, even though we're combining the translations,

而即使我哋綜合多個譯者

the site actually can translate pretty fast.

哩個網站嘅翻譯其實幾快

So let me show you,

等我展示一下

this is our estimates of how fast we could translate Wikipedia

哩個係估算我哋可以幾快咁將維基百科 從英文翻譯為西班牙文

from English into Spanish.

Remember, this is 50 million dollars' worth of value.

留意，哩度有五千萬美元嘅價值

So if we wanted to translate Wikipedia into Spanish,

如果我哋想將維基百科翻譯為西班牙文

we could do it in five weeks with 100,000 active users.

以 10 萬活躍用戶來計 我哋可以係 5 星期內完成

And we could do it in about 80 hours with a million active users.

以 100 萬活躍用戶來計 我哋可以喺 80 個鐘之內完成

既然我嘅團隊接觸嘅所有項目 都達到百萬用戶

Since all the projects my group has worked on so far

have gotten millions of users,

我哋希望可以用哩個項目極快咁翻譯

we're hopeful that we'll be able to translate extremely fast.

我對 Duolingo 最為興奮嘅係

Now, the thing that I'm most excited about with Duolingo

is I think this provides a fair business model for language education.

佢為語言教育提供咗 一種公平交易嘅商業模式

So here's the thing:

係咁樣嘅：

目前嘅語言教育模式係學生畀錢

The current business model for language education

is the student pays,

and in particular, the student pays Rosetta Stone 500 dollars.

即係學生會畀 500 美元 Rosetta Stone

(Laughter)

（笑聲）

That's the current business model.

哩就係目前嘅商業模式

The problem with this business model

哩種商業模式嘅問題係

is that 95 percent of the world's population doesn't have 500 dollars.

95% 嘅人口連 500 美元都冇

所以佢對貧窮人口係極唔公平嘅

So it's extremely unfair towards the poor.

This is totally biased towards the rich.

佢完全偏向富裕人口

Now, see, in Duolingo,

而且，因為你學緊語言嘅時候

because while you learn, you're actually creating value,

你實際上創造緊價值——

you're translating stuff --

你翻譯緊嗰啲本來需要錢翻譯嘅嘢

which, for example, we could charge somebody for translations,

so this is how we could monetize this.

哩個就係我哋貨幣化學習嘅方法

Since people are creating value while they're learning,

既然佢哋學習嘅時候創造緊價值

they don't have to pay with their money, they pay with their time.

佢哋無需付出金錢

只需要付出佢哋嘅時間

But the magical thing here

神奇在於你付出嘅時間 本來就係要來學語言嘅

is that is time that would have had to have been spent anyways

learning the language.

So the nice thing about Duolingo

所以我講 Duolingo 做嘅一件好事 就係提供咗一個公平嘅商業模式

is, I think, it provides a fair business model --

一個唔歧視貧窮嘅模式

one that doesn't discriminate against poor people.

Duolingo 就係哩個網站。多謝

So here's the site. Thank you.

(Applause)

（掌聲）

我哋仲未正式發佈

We haven't yet launched,

but if you go there, you can sign up to be part of our private beta,

但係如果你去哩個網站

你可以註冊成為非公開測試版本嘅一員

which is probably going to start in three or four weeks.

測試版本可能喺未來三四個星期 就會開始

We haven't yet launched it.

Duolingo 仲未有得用著

By the way, I'm the one talking here,

順便講一句，雖然係我喺度做哩個演講

but Duolingo is the work of a really awesome team,

但實際上 Duolingo 係一個出色團隊嘅產品

哩個團隊中嘅一些人今日都係哩度

some of whom are here. So thank you.

(Applause)

多謝！

（掌聲）