gmm_scoring¶
Copyright 20142019 Anthony Larcher and Sylvain Meignier
features_server
provides methods to test gmm models

gmm_scoring.
gmm_scoring
(ubm, enroll, ndx, feature_server, num_thread=1)[source]¶ Compute loglikelihood ratios for sequences of acoustic feature frames between a Universal Background Model (UBM) and a list of Gaussian Mixture Models (GMMs) which only mean vectors differ from the UBM.
 Parameters
ubm – a Mixture object used to compute the denominator of the likelihood ratios
enroll – a StatServer object which stat1 attribute contains mean supervectors of the GMMs to use to compute the numerator of the likelihood ratios.
ndx – an Ndx object which define the list of trials to compute
feature_server – a FeatureServer object to load the features
num_thread – number of thread to launch in parallel
 Returns
a Score object.

gmm_scoring.
gmm_scoring_singleThread
(ubm, enroll, ndx, feature_server, score_mat, seg_idx=None)[source]¶ Compute loglikelihood ratios for sequences of acoustic feature frames between a Universal Background Model (UBM) and a list of Gaussian Mixture Models (GMMs) which only mean vectors differ from the UBM.
 Parameters
ubm – a Mixture object used to compute the denominator of the likelihood ratios
enroll – a StatServer object which stat1 attribute contains mean supervectors of the GMMs to use to compute the numerator of the likelihood ratios.
ndx – an Ndx object which define the list of trials to compute
feature_server – sidekit.FeaturesServer used to load the acoustic parameters
score_mat – a ndarray of scores to fill
seg_idx – the list of unique test segments to process. Those test segments should belong to the list of test segments in the ndx object. By setting seg_idx=None, all test segments from the ndx object will be processed