iv_scoring

iv_scoring.PLDA_scoring(enroll, test, ndx, mu, F, G, Sigma)[source]

Compute the PLDA scores between to sets of vectors. The list of trials to perform is given in an Ndx object. PLDA matrices have to be pre-computed. i-vectors are supposed to be whitened before.

Parameters:
  • enroll – a StatServer in which stat1 are i-vectors
  • test – a StatServer in which stat1 are i-vectors
  • ndx – an Ndx object defining the list of trials to perform
  • mu – the mean vector of the PLDA gaussian
  • F – the between-class co-variance matrix of the PLDA
  • G – the within-class co-variance matrix of the PLDA
  • Sigma – the residual covariance matrix
Returns:

a score object

iv_scoring.cosine_scoring(enroll, test, ndx, wccn=None)[source]

Compute the cosine similarities between to sets of vectors. The list of trials to perform is given in an Ndx object.

Parameters:
  • enroll – a StatServer in which stat1 are i-vectors
  • test – a StatServer in which stat1 are i-vectors
  • ndx – an Ndx object defining the list of trials to perform
Returns:

a score object

iv_scoring.mahalanobis_scoring(enroll, test, ndx, M)[source]

Compute the mahalanobis distance between to sets of vectors. The list of trials to perform is given in an Ndx object.

Parameters:
  • enroll – a StatServer in which stat1 are i-vectors
  • ndx – an Ndx object defining the list of trials to perform
  • M – mahalanobis matrix as a ndarray
Parm test:

a StatServer in which stat1 are i-vectors

Returns:

a score object

iv_scoring.two_covariance_scoring(enroll, test, ndx, W, B)[source]

Compute the 2-covariance scores between to sets of vectors. The list of trials to perform is given in an Ndx object. Within and between class co-variance matrices have to be pre-computed.

Parameters:
  • enroll – a StatServer in which stat1 are i-vectors
  • test – a StatServer in which stat1 are i-vectors
  • ndx – an Ndx object defining the list of trials to perform
  • W – the within-class co-variance matrix to consider
  • B – the between-class co-variance matrix to consider
Returns:

a score object

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