<liclass="toctree-l2"><aclass="reference internal"href="hdf5.html">1. Save the features in HDF5 format</a></li>
<liclass="toctree-l2"><aclass="reference internal"href="featuresextractor.html">2. The FeaturesExtractor object</a></li>
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<liclass="toctree-l1"><aclass="reference internal"href="ubmTraining.html">Train a Universal Background Model</a><ul>
<liclass="toctree-l2"><aclass="reference internal"href="ubmTraining.html#training-using-em-split">1. Training using EM split</a></li>
<liclass="toctree-l2"><aclass="reference internal"href="ubmTraining.html#training-using-simple-em-with-fixed-number-of-distributions">2. Training using simple EM with fixed number of distributions</a></li>
<liclass="toctree-l2"><aclass="reference internal"href="ubmTraining.html#full-covariance-ubm">3 Full covariance UBM</a></li>
<liclass="toctree-l2"><aclass="reference internal"href="ubmTraining.html#training-using-em-split-on-several-nodes">3. Training using EM split on several nodes</a></li>
<liclass="toctree-l2"><aclass="reference internal"href="ubmTraining.html#full-covariance-ubm">4 Full covariance UBM</a></li>
</ul>
</li>
<liclass="toctree-l1"><aclass="reference internal"href="tv_estimation.html">Train an i-vector extractor</a><ul>
<liclass="toctree-l2"><aclass="reference internal"href="tv_estimation.html#using-a-single-process-on-one-machine">Using a single process on one machine</a></li>
<liclass="toctree-l2"><aclass="reference internal"href="tv_estimation.html#using-multiple-process-on-one-machine-with-python-multiprocessing">Using multiple process on one machine with Python MultiProcessing</a></li>
<liclass="toctree-l2"><aclass="reference internal"href="tv_estimation.html#using-multiple-process-on-multiple-nodes-with-mpi">Using multiple process on multiple nodes with MPI</a></li>
<liclass="toctree-l2"><aclass="reference internal"href="tv_estimation.html#get-to-know-the-algorithm-with-total-variability-raw">1. Get to know the algorithm with total_variability_raw</a></li>
<liclass="toctree-l2"><aclass="reference internal"href="tv_estimation.html#using-a-single-process-on-one-machine">2. Using a single process on one machine</a></li>
<liclass="toctree-l2"><aclass="reference internal"href="tv_estimation.html#using-multiple-process-on-one-machine-with-python-multiprocessing">3. Using multiple process on one machine with Python MultiProcessing</a></li>
<liclass="toctree-l2"><aclass="reference internal"href="tv_estimation.html#using-multiple-process-on-multiple-nodes-with-mpi">4. Using multiple process on multiple nodes with MPI</a></li>
</ul>
</li>
<liclass="toctree-l1"><aclass="reference internal"href="extractIVectors.html">Extract your I-Vectors</a><ul>
<liclass="toctree-l2"><aclass="reference internal"href="extractIVectors.html#extract-i-vectors-in-a-single-process">1. Extract i-vectors in a single process</a></li>
<liclass="toctree-l2"><aclass="reference internal"href="extractIVectors.html#extract-i-vectors-on-multiple-process-on-a-single-node">2. Extract i-vectors on multiple process on a single node</a></li>
<liclass="toctree-l2"><aclass="reference internal"href="extractIVectors.html#extract-i-vectors-on-multiple-nodes">3. Extract i-vectors on multiple nodes</a></li>
</ul>
</li>
<liclass="toctree-l1"><aclass="reference internal"href="extractIVectors.html">Extract your I-Vectors</a></li>
<liclass="toctree-l1"><aclass="reference internal"href="bnfExtraction.html">Bottleneck features extraction</a></li>
<liclass="toctree-l1"><aclass="reference internal"href="dnnStat.html">Phonetically aware Neural Network for speaker recognition</a></li>