title: Machine learning challenge: learn english pronunciation
body: <p>Say you want to take <a href="http://www.speech.cs.cmu.edu/cgi-bin/cmudict" rel="nofollow noreferrer">CMU's phonetic data set</a> input that looks like this:</p>
  
  <pre><code>ABERRATION  AE2 B ER0 EY1 SH AH0 N
  ABERRATIONAL  AE2 B ER0 EY1 SH AH0 N AH0 L
  ABERRATIONS  AE2 B ER0 EY1 SH AH0 N Z
  ABERT  AE1 B ER0 T
  ABET  AH0 B EH1 T
  ABETTED  AH0 B EH1 T IH0 D
  ABETTING  AH0 B EH1 T IH0 NG
  ABEX  EY1 B EH0 K S
  ABEYANCE  AH0 B EY1 AH0 N S
  </code></pre>
  
  <p>(The word is to the left, to the right are a series of phonemes, <a href="http://www.speech.cs.cmu.edu/cgi-bin/cmudict#about" rel="nofollow noreferrer">key here</a>)</p>
  
  <p>And you want to use it as training data for a machine learning system that would take new words and guess how they would be pronounced in English.</p>
  
  <p>It's not so obvious to me at least because there isn't a fixed token size of letters which could possible map to a phoneme. I have a feeling that something to do with a markov chain might be the right way to go.</p>
  
  <p>How would you do this?</p>