bob.machine.ISVBase

class bob.machine.ISVBase((object)self, (GMMMachine)ubm[, (int)ru=1]) → None :

Bases: bob.machine._machine.MachineGMMStatsScalarBase

An ISVBase instance can be seen as a container for U and D when performing Joint Factor Analysis (ISV).

References: [1] ‘Explicit Modelling of Session Variability for Speaker Verification’, R. Vogt, S. Sridharan, Computer Speech & Language, 2008, vol. 22, no. 1, pp. 17-38 [2] ‘Session Variability Modelling for Face Authentication’, C. McCool, R. Wallace, M. McLaren, L. El Shafey, S. Marcel, IET Biometrics, 2013

Builds a new ISVBase.

__init__( (object)self) -> None :
Constructs a 1 ISVBase instance. You have to set a UBM GMM and resize the U and D subspaces afterwards.
__init__( (object)self, (HDF5File)config) -> None :
Constructs a new ISVBaseMachine from a configuration file.
__init__( (object)self, (ISVBase)machine) -> None :
Copy constructs an ISVBase
__init__((object)self, (GMMMachine)ubm[, (int)ru=1]) → None :

Builds a new ISVBase.

__init__( (object)self) -> None :
Constructs a 1 ISVBase instance. You have to set a UBM GMM and resize the U and D subspaces afterwards.
__init__( (object)self, (HDF5File)config) -> None :
Constructs a new ISVBaseMachine from a configuration file.
__init__( (object)self, (ISVBase)machine) -> None :
Copy constructs an ISVBase

Methods

__init__((object)self, (GMMMachine)ubm [, …) Builds a new ISVBase.
forward((MachineGMMStatsScalarBase)self, …) Executes the machine on the GMMStats, and returns the (scalar) output.
forward_((MachineGMMStatsScalarBase)self, …) Executes the machine on the GMMStats, and returns the (scalar) output.
is_similar_to((ISVBase)self, …) Compares this ISVBase with the ‘other’ one to be approximately the same.
load((ISVBase)self, (HDF5File)config) Loads the configuration parameters from a configuration file.
resize((ISVBase)self, (int)ru) Reset the dimensionality of the subspaces U.
save((ISVBase)self, (HDF5File)config) Saves the configuration parameters to a configuration file.

Attributes

d The subspace D for residual variations
dim_c The number of Gaussian components
dim_cd The dimensionality of the supervector space
dim_d The dimensionality of the feature space
dim_ru The dimensionality of the within-class variations subspace (rank of U)
u The subspace U for within-class variations
ubm The UBM GMM attached to this Joint Factor Analysis model
__call__((MachineGMMStatsScalarBase)self, (GMMStats)input) → float :

Executes the machine on the GMMStats, and returns the (scalar) output. NO CHECK is performed.

d

The subspace D for residual variations

dim_c

The number of Gaussian components

dim_cd

The dimensionality of the supervector space

dim_d

The dimensionality of the feature space

dim_ru

The dimensionality of the within-class variations subspace (rank of U)

forward((MachineGMMStatsScalarBase)self, (GMMStats)input) → float :

Executes the machine on the GMMStats, and returns the (scalar) output.

forward_((MachineGMMStatsScalarBase)self, (GMMStats)input) → float :

Executes the machine on the GMMStats, and returns the (scalar) output. NO CHECK is performed.

is_similar_to((ISVBase)self, (ISVBase)other[, (float)r_epsilon=1e-05[, (float)a_epsilon=1e-08]]) → bool :

Compares this ISVBase with the ‘other’ one to be approximately the same.

load((ISVBase)self, (HDF5File)config) → None :

Loads the configuration parameters from a configuration file.

resize((ISVBase)self, (int)ru) → None :

Reset the dimensionality of the subspaces U.

save((ISVBase)self, (HDF5File)config) → None :

Saves the configuration parameters to a configuration file.

u

The subspace U for within-class variations

ubm

The UBM GMM attached to this Joint Factor Analysis model