<p>You can rephrase your question as a statistical problem, where you for each word or n-gram try to predict the most likely correctly spelled version of each word or n-gram based on your knowledge of the distributions of these across a corpus of text in the target language.</p>

<p>This is how spell-checkers work.</p>

<p>Peter Norvig (who wrote <em>Artificial Intelligence: A Moderne Approach</em> with Stuart Russell) has an article on the this with a short, easy-to-read code example and a description of the statistics behind it on his web page: <a href="http://norvig.com/spell-correct.html" rel="nofollow noreferrer" title="How to write a Spelling Corrector">How to write a Spelling Corrector</a>.</p>

CC BY-SA 3.0
2017-11-05T21:06:49.297Z
2017-11-05T21:06:49.297Z
mjul
<p>Given an ease with which a human can read a text scrambled in a special way, like the following passage popular a while ago</p>

<blockquote>
  <p>Aoccdrnig to a rscheearch at Cmabrigde Uinervtisy, it deosn't mttaer
  in waht oredr the ltteers in a wrod are, the olny iprmoatnt tihng is
  taht the frist and lsat ltteers be at the rghit pclae. The rset can be
  a toatl mses and you can sitll raed it wouthit porbelm. Tihs is
  bcuseae the huamn mnid deos not raed ervey lteter by istlef, but the
  wrod as a wlohe.</p>
</blockquote>

<p>could you train a computer to restore the original? Are there any studies/known instruments that can achieve this?</p>

<p>I am talking about mildly scrambled/damaged text, like the above, not a totally random permutations or random omission of letters.</p>

<machine-learning>
Is it possible to restore scrambled/damaged text?
Yrogirg
# Is it possible to restore scrambled/damaged text?

(Asked by: username_0 on 2017-11-05)

Given an ease with which a human can read a text scrambled in a special way, like the following passage popular a while ago

> Aoccdrnig to a rscheearch at Cmabrigde Uinervtisy, it deosn't mttaer
> in waht oredr the ltteers in a wrod are, the olny iprmoatnt tihng is
> taht the frist and lsat ltteers be at the rghit pclae. The rset can be
> a toatl mses and you can sitll raed it wouthit porbelm. Tihs is
> bcuseae the huamn mnid deos not raed ervey lteter by istlef, but the
> wrod as a wlohe.

could you train a computer to restore the original? Are there any studies/known instruments that can achieve this?

I am talking about mildly scrambled/damaged text, like the above, not a totally random permutations or random omission of letters.

**Tags:** machine-learning


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## 1 answers

### Answer by username_1 on 2017-11-05. Score: 2

You can rephrase your question as a statistical problem, where you for each word or n-gram try to predict the most likely correctly spelled version of each word or n-gram based on your knowledge of the distributions of these across a corpus of text in the target language.

This is how spell-checkers work.

Peter Norvig (who wrote *Artificial Intelligence: A Moderne Approach* with Stuart Russell) has an article on the this with a short, easy-to-read code example and a description of the statistics behind it on his web page: [How to write a Spelling Corrector](http://norvig.com/spell-correct.html "How to write a Spelling Corrector").


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