Baseline class for outlier elimination parameters
Single Gaussian based outlier elimination.
Parameters for single Gaussian based outlier elimination
TO DO: GMM based outlier elimination
K-Means clustering and mapping based outlier elimination.
This class implements a K-Means clustering and mapping based outlier elimination procedure: - Step1: Cluster source and target acoustic features either jointly or separately - Step2: For each feature, for each source cluster find the most likely target cluster - Step3: For each feature, for each target cluster find the most likely source cluster - Step4: Determine outlier pairs by checking the total number of source-target pairs assigned to clusters other than the most likely cluster which are sufficiently "distant" from the most likely cluster
Class for keeping total standard deviations to be used in automatic thresholding in outlier elimation
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