title: Converting from one MFCC type to another - HTK
body: <p>I am working with the <code>HTK</code> toolkit on a word spotting task and have a classic training and testing data mismatch. The training data consisted of only "clean" (recorded over a mic) data. The data was converted to <code>MFCC_E_D_A</code> parameters which were then modelled by HMMs (phone-level). My test data has been recorded over landline and mobile phone channels (inviting distortions and the like). Using the <code>MFCC_E_D_A</code> parameters with <code>HVite</code> results in incorrect output. I want to make use of <code>cepstral mean normalization</code> with <code>MFCC_E_D_A_Z</code> parameters but it would not be of much use since the HMMs are not modelled with this data. My questions are as follows:  </p>
  
  <ol>
  <li>Is there any way by which I can <strong><em>convert</em></strong> <code>MFCC_E_D_A_Z</code> into <code>MFCC_E_D_A</code>? That way I follow this way: <code>input -&gt; MFCC_E_D_A_Z -&gt; MFCC_E_D_A -&gt; HMM log likelihood computation</code>.  </li>
  <li>Is there any way to convert the existing HMMs which model <code>MFCC_E_D_A</code> parameters into <code>MFCC_E_D_A_Z</code>?  </li>
  </ol>
  
  <p>If there is a way to do (1) from above, what would the config file for <code>HCopy</code> look like? I wrote the following <code>HCopy</code> config file for conversion:<br>
  <code>
  SOURCEFORMAT = MFCC_E_D_A_Z<br>
  TARGETKIND = MFCC_E_D_A<br>
  TARGETRATE = 100000.0<br>
  SAVECOMPRESSED = T<br>
  SAVEWITHCRC = T<br>
  WINDOWSIZE = 250000.0<br>
  USEHAMMING = T<br>
  PREEMCOEF = 0.97<br>
  NUMCHANS = 26<br>
  CEPLIFTER = 22<br>
  NUMCEPS = 12<br>
  ENORMALISE = T</code></p>
  
  <p>This does not work. How can I improve this?</p>