gmm_scoring

gmm_scoring.gmm_scoring(ubm, enroll, ndx, feature_server, numThread=1)

Compute log-likelihood 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 super-vectors 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
• numThread – number of thread to launch in parallel

Returns:

a Score object.

gmm_scoring.gmm_scoring_singleThread(ubm, enroll, ndx, feature_server, scoreMat, segIdx=None)

Compute log-likelihood 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 super-vectors 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
• featureDir – path of the directory containing the feature files
• featureFormat – format of the feature files to load. Can be: - SPRO4 (see http://www.irisa.fr/metiss/guig/spro/) - HTK (see http://htk.eng.cam.ac.uk)
• featureExtension – extension of the feature files to load
• scoreMat – a ndarray of scores to fill
• segIdx – 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 segIdx=None, all test segments from the ndx object will be processed