未登录,请登录后再发表信息
最新评论 (0)
播放视频

某些单词是如何被遗忘的?

How Some Words Get Forgetted

[Intro Music Playing]
[开场乐]
Hey smart people, Joe here.
智者们好 我是Joe
In your whole life, how many books have you “readed”?
目前为止 你“readed”(读过)过几本书呢?
Sorry, I mean “read”.
抱歉 是“read(读了)”
But not “red”, like the color.
不是“red(红色)”
“Read” like the past tense of “read”.
是“read”的过去式
I just “misspeaked”.
刚刚“misspeaked”(口误)了
“Mispoke”.
应该是“Mispoke”
This reminds me of a poem:
这让我想起了一首诗:
“The verbs in English are a fright.
“英语动词骇人听闻
How can we learn to read and write?
如何练就读写技能?
Today we write, but first we wrote;
单词变形换拼写
We bite our tongues, but never bote.
语音变化舌打结
This tale I tell; this tale I told;
时态是否都正确
I smell the flowers, but never smold.
规则牢记于心中
If I still do as once I did,
人生尚可复又重
Then do cows moo, as they once mid?”
古今牛声却不同”
That was penned by linguist Richard Lederer.
本诗出自语言学家Richard Lederer之笔
And it’s proof that English is weird.
佐证了英语的奇怪之处
We can blame all this confusion on irregular verbs.
我们可以将其统统归咎于不规则动词
Most verbs in English are regular.
大多数英语动词的变化是规则的
We make their past tense by adding a letter or two on the end.
在词尾增加一两个字母就能变成过去式
There’re the difference between what “happens” now and what “happened”.
譬如what “happens” now(现在时)与what “happened”(过去时)
But irregular verbs are…well, not regular.
但不规则动词嘛…就不规则啦
Like there are difference between what “is” and what “was”.
譬如what “is”(现在时)与what “was”(过去时)
It’s cute when kids say,
小孩会童真地说
“I ‘breaked’ my toy.”
“I ‘breaked’ my toy”
But why do the rest of us say “broke”?
但为何我们用“broke”?
Because that’s just what everyone else says, right?
因为大势所趋 是吗?
We say it how it’s always been said.
大家都是这么用的
But if we were thinking scientifically,
但若我们科学地思考一下
we’d ask, “How did it get this way?”
就会产生疑惑:“语言怎么发展到这一步的?”
And I don’t know about you,
我不了解你
but I prefer to think scientifically.
但我喜欢科学地思考
A biologist studies how things are by looking at how they used to be.
生物学家通过研究事物的过去 来了解现在
We find fossils.
比如研究化石
But how does one go about finding a fossil of language?
但语言哪有化石可以研究呢?
Well luckily, people tend to write language down.
幸好 语言被人们用文字记载下来
James Joyce’s Ulysses contains 265,222 words.
詹姆斯·乔伊斯的《尤利西斯》共265,222词
I totally counted and didn’t just google that.
我自己算的 没有google哦
[Clicking]
[鼠标点击]
[Clicking]
[鼠标点击]
Of those words,
在这些词中
the word “time” is the 74th most frequent,
“time”出现频率位于第74位
used 376 times.
共使用376次
The word “the” is the most frequently used, 14,877 times.
“the”的使用频率最高 达14,877次
We know that thanks to another type of book: a Concordance,
这些统计全要归功于:用词索引书
an index of words that lists every instance of every word in a written work.
它会列举某个作品中所有词的索引数据
There’s Concordances for Thoreau’s Walden,
在梭罗的《瓦尔登湖》的索引中
he enjoyed the “woods” more than the “forest”,
发现他偏向于使用“woods”而非“forest”
the poetry of Edgar Allan Poe,
在爱伦坡的诗歌索引中
where we find the “raven” more than “eldorado”,
发现“raven”的词频比“eldorado”高
the writings of Descartes in the original French,
笛卡尔的法文论著
even the Bible.
甚至是《圣经》都有相应的索引书
A linguist named George Kingsley Zipf looked at these ranked lists of written language
语言学家George Kingsley Zipf研究这些书面语的索引数据
and noticed something funny:
发现了一个有趣的现象:
Not all words are created equal.
并非所有词生来平等
Some get used a lot,
有些词使用频率高
while most almost never get used.
有些则几乎不使用
Like how we say “the” all the time,
比如我们常说“the”
but almost never say “hallux”,
但从不说“hallux”
the anatomical name for your big toe.
也就是大脚趾的解剖学名
When it comes to a trait like height,
对于人的身高
most people are pretty close to average,
大多数人位于平均水平左右
while the very tallest people are only maybe three times taller than the shortest.
最高者的身高仅仅是最低者的3倍左右
We don’t vary very much.
人类的身高变化并不大
Height is normal.
而且变化有规律
It’s literally a normal distribution.
呈正态曲线分布
But Zipf realized words are abnormal.
但Zipf认识到单词的不规则性
Only a few words are very common,
使用频率高的词很少
while most words are very uncommon.
少用的词则数不胜数
For instance, in Ulysses,
比如 在《尤利西斯》中
there are a thousand words used more than 26 times,
使用次数超过26次的单词有1,000个
a hundred words used more than 265 times,
使用次数超过265次的单词有100个
but only ten words used more than 2,653 times.
使用次数超过2,653次的单词仅有10个
Another way to say this:
换句话说:
The 10th most frequently used word is ten times more common
第10名单词的索引词频是
than the 100th most used.
第100名的10倍
This peculiar trend is called Zipf’s Law.
这种独特的关系称作“Zipf定律”
-And the…What the… -Hey! Tacky here!
-然后…什么… -大家好 我是Tacky
It looks like you’re talking about Zipf’s Law.
你好像在讲Zipf定律呀
Did you know Vsauce already did a video about that?
你知道《Vsauce》(科普短片)也做过关于它的内容吗?
Yeah, it’s a great video.
知道 讲的还不赖
It’s actually what got me thinking about this,
正是它引发了我的思考
but I’m gonna tell them about more than Zipf’s Law.
但我会拓展的更多一些
-I want to also… -Would you like me to help you click over to that video?
-我想… -要我帮你打开那个视频吗?
No! No!
别!别!
I want you to watch this video,
请大家不要走开
but if you DID watch Michael’s video on Vsauce,
即便你确实看过Michael在《Vsauce》里的讲解
perhaps by clicking a link in the description,
点击我们的相关链接
later you’d learn that Zipf’s Law applies to tons of stuff,
你会发现Zipf定律应用于各类事物
like wealth, the population of cities,
比如财富 城市人口数量
how long audiences clap,
观众鼓掌时间
web traffic, the size of holes in Swiss cheese,.
网站流量 瑞士奶酪洞的大小
and especially language.
尤其是语言
Wherever people look, newspapers, other languages,
无论人们阅读什么 报纸还是外语
even randomly generated words,
甚至是即兴创造的单词
pretty much everything in language obeys Zipf’s Law.
几乎一切语言都遵循Zipf定律
Well, everything except irregular verbs.
除了不规则动词
The 12 most common verbs in the English language are:
英语中最常见的12个动词:
be, have, do, say, get, make,
be have do say get make
go, know, take, see, come, and think,
go know take see come和think
all irregular.
均为不规则动词
But irregulars are a tiny fraction of all verbs.
它们在所有动词中占比极低
English only has around 200 irregular verbs,
英语大约只有200个不规则动词
a mere 3 percent of total verbs.
仅占所有动词总数的3%
Instead of having a few commonly used irregular verbs and lots of rare ones,
根据Zipf定律 常见的不规则动词很少
like Zipf’s Law predicts,
大多数几乎不使用
almost all irregular verbs are common,
但几乎所有的不规则动词都很常见
and almost none are rare.
几乎都会使用
Irregular verbs are “Zipf exception”.
Zipf定律不适用于不规则动词
[Music]
[音乐]
That’s really hard to do.
这很难做到耶
Where do irregular verbs come from?
不规则动词是怎么来的?
They’re the oldest ones we have.
它们的历史可以追溯到
Around four to six thousand years ago,
4,000至6,000年前
people stretching from Europe to Western Asia
在欧洲至西亚一带
spoke an ancient language known as Proto Indo European.
人们说着原始印欧语
A staggering number of modern languages descend from this.
它是多种现代语言的祖先
In PIE, the meaning and tense of words could be changed
其词语的意思和时态
through a system where vowel sounds were swapped.
通过元音音变系统实现变化
This system, the Ablaut, can still be heard today in irregular verbs:
此系统Ablaut还影响着如今的某些不规则动词:
dig, dug,
如dig dug
sing, sang, sung.
sing sang sung
At the time, it was just one of many competing systems for changing verbs.
当时Ablaut只是动词变化的众多系统之一
But a bit later, people speaking Proto Germanic,
不久后 出现原始日耳曼语
a dialect descended from PIE,
这种源于原始印欧语的方言
began adding verbs to the language that didn’t fit these old patterns,
创造的动词不再适合原有的动词变化系统
so they invented a new way of signifying the past tense
因此产生了一套全新的动词变化规则
by simply adding “-t” or “-ed” sounds to the end.
即在动词后加“-t”或“-ed”音
Back then, these new “regular” verbs were actually the exception.
当时 这些新出现的“规则动词”并非主流
As English grew from this Proto Germanic language,
当英语逐渐从原始日耳曼语中分离
newly added words became automatically regular,
英语的新动词自动规则化
They followed this new rule.
遵循新的变化规则
And many older verbs began to switch from the old way to the new,
许多古老的动词也逐步规则化
Like how long ago, the knight slew the dragon,
比如以前我们说 “the knight ‘slew’ the dragon”
but Beyoncé slayed at her last show.
现在变为“Beyoncé ‘slayed’ at her last show”
By the time the old English story of Beowulf was written,
古英语时期作品《贝奥武夫》完成时
three out of every four verbs had been regularized.
75%的动词已被规则化
There were a handful of verbs that moved in the other direction,
还有部分动词往另一方向发展
going from regular to irregular,
变为不规则动词
but for every “haved” or “maked” that was “had” or “made”,
即便“haved”变为“had” 或“maked”变为“made”
there are dozens of verbs like “holp” that got “helped” along.
更多的动词像“holp”变为“helped” 在被规则化
Regular was no longer the exception.
规则化已成为主流
It was the rule.
是变化的原则
So why did some irregular verbs go extinct,
为什么某些不规则动词会消失
while others have survived?
而某些还在使用?
We all know that language evolves,
我们都知道语言会进化
similar to how living things do, changing slightly over time.
就像生物一样 随时间逐渐演化
Could language also undergo some kind of natural selection?
那么有无可能语言也经历着自然选择?
I mean is there something about a word that decides whether it’s strong enough to live on?
有无单词是通过是否常用来决定去留呢?
We can test this.
我们可以试验一下
We just need a bigger data set than one book.
只需要一份大于一本书的索引容量
Using ancient grammar textbooks along with databases of millions of written words,
研究员利用古语法书和数百万个书面用词索引
researchers tracked the evolution of 177 verbs that were irregular at the time Beowulf was written.
跟踪了《贝奥武夫》写就时期的177个不规则动词的变化
By the time Chaucer wrote Canterbury Tales,
到乔叟的《坎特伯雷故事集》写就时
32 of these had become regular.
其中有32个变为规则动词
By the time we hit modern English,
现代英语出现时
79 had regularized.
79个已被规则化
The trait that predicted whether or not a verb would become regular was how often we use it.
判断动词是否规则变化的依据是其使用频率
The most frequently used verbs tend to stay irregular.
使用频率越高则越不规则
The most rarely used become regular.
反之越规则
Surprisingly, there was a sort of hidden Zipfian pattern there after all.
令人惊讶的是 这与Zipf定律不谋而合
If a verb is used 100 times less frequently,
若一个动词的使用次数少于100次
it will regularize 10 times as fast.
它被规则化的速度会加快10倍
If they’re used 10,000 times less frequently,
若使用频率少于10,000次
they’ll regularize 100 times as fast.
它被规则化的速度会加快100倍
Researchers were able to estimate the likely lifespan of irregular verbs.
研究员可据此估计不规则动词的大概使用期限
A word like “stink”, that’s used once every 10,000 to 100,000 words,
比如说“stink”在10,000至100,000个单词中出现一次
has a 50% chance of regularizing within 700 years.
有50%的可能在700年内会被规则化
“Drink”, a more common word, will take more like 5,000 years.
“drink”更常见些 大概寿命为5,000年
We can find words today in the process of going extinct.
我们还可以推断正濒临灭绝的单词
Do you tend to say “dived” or “dove”?
思考一下 你用“dived”还是“dove”?
Now is your last chance to be newly “wed”.
你用“wed”多一些
Pretty soon, you might be newly “wedded”.
还是“wedded”?
“Wed” is the irregular verb we think will most likely disappear next.
下一个消失的不规则动词很有可能是“wed”
This seems to be natural selection for a language.
这看起来像是语言的自然选择
Usage frequency affects a word’s survival,
词的使用频率会影响其存亡
and this makes sense.
这并不难理解
Regular verbs follow a rule.
规则动词的变化有规律可循
When we encounter a word we don’t know,
即便我们不认识它
we can still figure out its past tense,
也能推断出其过去式
without memorizing each and every one.
因此不需要过多的记忆
Irregular verbs on the other hand, have to be memorized.
不规则动词则需要记忆
If we don’t use them, we lose them.
若我们不用它 它就会消失
As they’re slowly forgotten,
不规则动词被遗忘的过程
the “regular” rule is used in their place.
也是被逐步规则化的过程
In 1980, after thirty years of work,
经过30年的努力 在1980年
IBM was able to digitize the complete works of Thomas Aquinas.
IBM已能把托马斯·阿奎纳的所有著作数字化
Today, it’s something that you or anyone who knows how to code
如今 只要会编码
can do in a few minutes,
任何人都能用键盘
with just a few keystrokes.
快速做到图书数字化
Concordances, the indexes of language
索引书 这个引发Zipf和许多人
that inspired Zipf and others to ask these questions,
思考这些问题的语言索引
no one really writes those anymore.
已再无后人书写
Except maybe they do.
除非有谁自告奋勇
It’s called “Google”.
它就是“Google”
A search engine is basically a list of words and phrases from around the web,
Google是索引网络和网页界面关键字
and the pages where they appear.
的搜索引擎
Concordances were just analog Google.
模拟索引书的作用
The Google Books Project now contains 25 million scanned books stretching back more than 500 years.
谷歌图书可扫描500年前至今的25,000,000本书
No matter how many books you read,
即便学富五车
you could never read every book,
学海无边 书囊无底
or even a fraction of them in a lifetime.
世间书怎读得尽
If you tried to read just the English language books
若自2000年起
from the year 2000 in this collection, at a reasonable pace without stopping,
以正常速度不间断地阅读所有谷歌图书
it would take you 80 years.
需要足足80年
But what could we learn if we made computers read for us?
若电脑帮我们读书 我们能从中获益吗?
The Google Ngram Viewer is a search tool we can use to study
Google Ngram Viewer是一款搜索工具
how human culture has changed over the centuries.
用来研究人类文化的变迁
It plots the frequency of strings of one or more words by year
它绘制了数百万本数字化书籍中
found in those millions of digitized books.
一个或多个单词每年出现的频率图
We can see when people stopped talking about the “Great War”,
从中可以看出人们何时不再用“Great War”表示一战
and started calling it World War I instead.
而用“World War I”
“Evolution” was on the decline until “DNA” came along.
在“DNA”这个词出现前 “Evolution”的词频一直在下降
Einstein took “physics” to the next level.
爱因斯坦把“physics”的使用频率推向高峰
People like “pizza” more than “hamburgers”,
“pizza”比“hamburgers”的词频高
but less than “ice cream”.
但仍比不上“ice cream”
What’s the most interesting one you can find?
你又有什么有趣的发现呢?
Of course, as much data as we can pull from millions of digitized books,
在数百万本数字化书籍中汲取数据
like how verbs evolve or culture changes over time,
了解动词的演变与文化的变迁
we haven’t read them.
都无需我们亲自阅读
A computer has.
用电脑即可
And while it gives us access to an immense amount of data,
纵使电脑拥有强大的数据库
the reason we read isn’t the words.
我们阅读的目的不是单词
It’s the story.
而是故事
Stay curious.
所以 请保持好奇心
Hey guys, if you thought Google’s Ngram Viewer look pretty cool,
若大家觉得Google Ngram Viewer好用
or Sarah over the Art Assignment used it to look at how and when
或好奇《 Art Assignment》中的Sarah
different artists got famous or not.
是否用它来了解艺术家的成名时间与方式
You can link the description to that one too.
你也可以点击相关链接
Also I want to tell you about the Great American Read.
我想向你介绍Great American Read
It’s a new series on PBS about why we love to read,
这是PBS的新系列内容 探讨我们爱阅读的原因
leading up to a vote on America’s favourite novel.
并选出美国最受欢迎的小说
Who decides America’s favourite novel?
谁来决定美国最受欢迎的小说?
That would be you!
就是你了!
Head to pbs.org/greatamericanread to vote on your favourite book.
登录pbs.org/greatamericanread 为你喜爱的书投票
Click link in the description for more details.
点击相关链接 了解更多内容

发表评论

译制信息
视频概述

在人类进程和语言的演化中,不被使用的单词会走向灭绝。

听录译者

收集自网络

翻译译者

Seline

审核员

审核员A

视频来源

https://www.youtube.com/watch?v=tFW7orQsBuo

相关推荐