Cepwin Features Training

Recently the option to bypass delta and delta-delta feature extraction process and directly apply LDA transform matrix to the cepstrum coefficients of sequential frames was added to sphinxtrain. To use it you need to adjust training config and decoder as well:

  • Set feature type to 1s_c
  • Add $CFG_FEAT_WINDOW=3; to the config file
  • Train with MLLT
  • Apply the attached patch to sphinxbase cepwin.diff.
  • Decode

  • You can use these models in sphinx4 now, the following config should do the work:

    <component name="featureExtraction" type="edu.cmu.sphinx.frontend.feature.ConcatFeatureExtractor">
    <property name="windowSize" value="3"/>
    </component>
    <component name="lda" type="edu.cmu.sphinx.frontend.feature.LDA">
    <property name="loader" value="sphinx3Loader"/>
    </component>

    I haven't found the optimal parametrers yet, but it seems that something like cepwin=3 and final dimension around 40 should work. I hope to get results on this soon.

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