bob.machine.JFABase

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

Bases: bob.machine._machine.MachineGMMStatsScalarBase

A JFABase instance can be seen as a container for U, V and D when performing Joint Factor Analysis (JFA).

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 JFABase.

__init__( (object)self) -> None :

Constructs a 1x1 JFABase instance. You have to set a UBM GMM and resize the U, V and D subspaces afterwards.

__init__( (object)self, (HDF5File)config) -> None :

Constructs a new JFABaseMachine from a configuration file.

__init__( (object)self, (JFABase)machine) -> None :

Copy constructs a JFABase

__init__((object)self, (GMMMachine)ubm[, (int)ru=1[, (int)rv=1]]) → None :

Builds a new JFABase.

__init__( (object)self) -> None :

Constructs a 1x1 JFABase instance. You have to set a UBM GMM and resize the U, V and D subspaces afterwards.

__init__( (object)self, (HDF5File)config) -> None :

Constructs a new JFABaseMachine from a configuration file.

__init__( (object)self, (JFABase)machine) -> None :

Copy constructs a JFABase

Methods

__init__((object)self, (GMMMachine)ubm [, …)	Builds a new JFABase.
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((JFABase)self, …)	Compares this JFABase with the ‘other’ one to be approximately the same.
load((JFABase)self, (HDF5File)config)	Loads the configuration parameters from a configuration file.
resize((JFABase)self, (int)ru, (int)rv)	Reset the dimensionality of the subspaces U and V.
save((JFABase)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)
dim_rv	The dimensionality of the between-class variations subspace (rank of V)
u	The subspace U for within-class variations
ubm	The UBM GMM attached to this Joint Factor Analysis model
v	The subspace V for between-class variations

__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)

dim_rv

The dimensionality of the between-class variations subspace (rank of V)

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

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

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

Loads the configuration parameters from a configuration file.

resize((JFABase)self, (int)ru, (int)rv) → None :

Reset the dimensionality of the subspaces U and V.

save((JFABase)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

v

The subspace V for between-class variations