Functions

agglomerative_cluster Calls C++ function
compute_vad_energy Calls C++ function
estimate_ivectors_online Obtains periodically an estimate of the iVector including all frames up to that point.

Classes

AgglomerativeClusterer CLIF wrapper for ::kaldi::AgglomerativeClusterer
AhcCluster CLIF wrapper for ::kaldi::AhcCluster
IvectorEstimationOptions Options for estimating iVectors, during both trainning and test.
IvectorExtractor CLIF wrapper for ::kaldi::IvectorExtractor
IvectorExtractorEstimationOptions CLIF wrapper for ::kaldi::IvectorExtractorEstimationOptions
IvectorExtractorOptions CLIF wrapper for ::kaldi::IvectorExtractorOptions
IvectorExtractorStats CLIF wrapper for ::kaldi::IvectorExtractorStats
IvectorExtractorStatsOptions CLIF wrapper for ::kaldi::IvectorExtractorStatsOptions
IvectorExtractorUtteranceStats Stats for a particular utterance, i.e., the sufficient stats for estimating an iVector
LogisticRegression CLIF wrapper for ::kaldi::LogisticRegression
LogisticRegressionConfig CLIF wrapper for ::kaldi::LogisticRegressionConfig
OnlineIvectorEstimationStats CLIF wrapper for ::kaldi::OnlineIvectorEstimationStats
Plda CLIF wrapper for ::kaldi::Plda
PldaConfig CLIF wrapper for ::kaldi::PldaConfig
PldaEstimationConfig CLIF wrapper for ::kaldi::PldaEstimationConfig
PldaStats CLIF wrapper for ::kaldi::PldaStats
PldaUnsupervisedAdaptor CLIF wrapper for ::kaldi::PldaUnsupervisedAdaptor
PldaUnsupervisedAdaptorConfig CLIF wrapper for ::kaldi::PldaUnsupervisedAdaptorConfig
VadEnergyOptions CLIF wrapper for ::kaldi::VadEnergyOptions
class kaldi.ivector.AgglomerativeClusterer

CLIF wrapper for ::kaldi::AgglomerativeClusterer

cluster() → list<int>

Calls C++ function void ::kaldi::AgglomerativeClusterer::Cluster(::std::vector< ::int32>*)

class kaldi.ivector.AhcCluster

CLIF wrapper for ::kaldi::AhcCluster

id

C++ ::int32 AhcCluster.id

parent1

C++ ::int32 AhcCluster.parent1

parent2

C++ ::int32 AhcCluster.parent2

size

C++ ::int32 AhcCluster.size

utt_ids

C++ ::std::vector< ::int32> AhcCluster.utt_ids

class kaldi.ivector.IvectorEstimationOptions

Options for estimating iVectors, during both trainning and test.

acoustic_weight

C++ double IvectorEstimationOptions.acoustic_weight

max_count

C++ double IvectorEstimationOptions.max_count

register(opts:OptionsItf)

Calls C++ function void ::kaldi::IvectorEstimationOptions::Register(::kaldi::OptionsItf *)

CLIF wrapper for ::kaldi::IvectorExtractor

Calls C++ function int ::kaldi::IvectorExtractor::FeatDim()

Returns the part of the acoustic auxf that relates to the gconsts of the Gaussian.

Returns just the part of the acoustic auxf that relates to the speaker-dependent means

Returns just the part of the acoustic auxf that relates to the variance of the utt_stats.

Returns the part of the acoustic auxf that relates to the Gaussian-specific weights.

Returns the data-dependent part of the log-likelihood objective function, summed over frames.

Get the linear and quadratic terms in the distribution over iVectors

Gets the linear and quadratic terms in the distribution over iVectors that arise from the prior.

Gets the linear and quadratic terms in the distribution over iVectors that arise from the weights

Gets the distribution over ivectors (or the Gaussian approximation).

Parameters:

Returns the prior-related part of the log-likelihood objective function.

Calls C++ function bool ::kaldi::IvectorExtractor::IvectorDependentWeights()

Calls C++ function int ::kaldi::IvectorExtractor::IvectorDim()

Calls C++ function std::unique_ptr<::kaldi::IvectorExtractor> ::kaldi::IvectorExtractor::IvectorExtractor(::kaldi::IvectorExtractorOptions, ::kaldi::FullGmm)

Calls C++ function int ::kaldi::IvectorExtractor::NumGauss()

Offset of first dimension.

Calls C++ function void ::kaldi::IvectorExtractor::Read(::std::basic_istream<char, ::std::char_traits<char> >, bool)

Calls C++ function void ::kaldi::IvectorExtractor::Write(::std::basic_ostream<char, ::std::char_traits<char> >, bool)

CLIF wrapper for ::kaldi::IvectorExtractorEstimationOptions

C++ bool IvectorExtractorEstimationOptions.diagonalize

C++ double IvectorExtractorEstimationOptions.gaussian_min_count

C++ ::int32 IvectorExtractorEstimationOptions.num_threads

Calls C++ function void ::kaldi::IvectorExtractorEstimationOptions::Register(::kaldi::OptionsItf *)

C++ double IvectorExtractorEstimationOptions.variance_floor_factor

CLIF wrapper for ::kaldi::IvectorExtractorOptions

C++ int IvectorExtractorOptions.ivector_dim

C++ int IvectorExtractorOptions.num_iters

Calls C++ function void ::kaldi::IvectorExtractorOptions::Register(::kaldi::OptionsItf *)

C++ bool IvectorExtractorOptions.use_weights

CLIF wrapper for ::kaldi::IvectorExtractorStats

Calls C++ function void ::kaldi::IvectorExtractorStats::AccStatsForUtterance(::kaldi::IvectorExtractor, ::kaldi::MatrixBase<float>, ::kaldi::Posterior)

Calls C++ function void ::kaldi::IvectorExtractorStats::Add(::kaldi::IvectorExtractorStats)

Calls C++ function double ::kaldi::IvectorExtractorStats::AuxfPerFrame()

Prints the proportion of the variance explained by the Ivector model versus the Gaussians.

Calls C++ function std::unique_ptr<::kaldi::IvectorExtractorStats> ::kaldi::IvectorExtractorStats::IvectorExtractorStats(::kaldi::IvectorExtractor, ::kaldi::IvectorExtractorStatsOptions)

Calls C++ function void ::kaldi::IvectorExtractorStats::Read(::std::basic_istream<char, ::std::char_traits<char> >, bool)

Returns the objf improvement per frame

Calls C++ function void ::kaldi::IvectorExtractorStats::Write(::std::basic_ostream<char, ::std::char_traits<char> >, bool)

CLIF wrapper for ::kaldi::IvectorExtractorStatsOptions

C++ int IvectorExtractorStatsOptions.cache_size

C++ bool IvectorExtractorStatsOptions.compute_auxf

C++ ::int32 IvectorExtractorStatsOptions.num_samples_for_weights

Calls C++ function void ::kaldi::IvectorExtractorStatsOptions::Register(::kaldi::OptionsItf *)

C++ bool IvectorExtractorStatsOptions.update_variances

Stats for a particular utterance, i.e., the sufficient stats for estimating an iVector

Calls C++ function void ::kaldi::IvectorExtractorUtteranceStats::AccStats(::kaldi::MatrixBase<float>, ::kaldi::Posterior)

Calls C++ function std::unique_ptr<::kaldi::IvectorExtractorUtteranceStats> ::kaldi::IvectorExtractorUtteranceStats::IvectorExtractorUtteranceStats(int, int, bool)

Calls C++ function double ::kaldi::IvectorExtractorUtteranceStats::NumFrames()

Calls C++ function void ::kaldi::IvectorExtractorUtteranceStats::Scale(double)

class kaldi.ivector.LogisticRegression

CLIF wrapper for ::kaldi::LogisticRegression

get_log_posteriors_matrix(xs:Matrix) → Matrix

Calculates the log posterior of the class label given the input xs

get_log_posteriors_vector(x:Vector) → Vector

Calculates the log posterior of the class label given the input x.

read(os:istream, binary:bool)

Calls C++ function void ::kaldi::LogisticRegression::Read(::std::basic_istream<char, ::std::char_traits<char> >, bool)

scale_priors(prior_scales:Vector)

Calls C++ function void ::kaldi::LogisticRegression::ScalePriors(::kaldi::Vector<float>)

train(xs:Matrix, ys:list<int>, conf:LogisticRegressionConfig)

xs and ys are the trainning data. Each row of xs is a vector corresponding to the class label in the same row of ys.

write(os:ostream, binary:bool)

Calls C++ function void ::kaldi::LogisticRegression::Write(::std::basic_ostream<char, ::std::char_traits<char> >, bool)

class kaldi.ivector.LogisticRegressionConfig

CLIF wrapper for ::kaldi::LogisticRegressionConfig

max_steps

C++ ::int32 LogisticRegressionConfig.max_steps

mix_up

C++ ::int32 LogisticRegressionConfig.mix_up

normalizer

C++ double LogisticRegressionConfig.normalizer

power

C++ double LogisticRegressionConfig.power

register(opts:OptionsItf)

Calls C++ function void ::kaldi::LogisticRegressionConfig::Register(::kaldi::OptionsItf *)

class kaldi.ivector.OnlineIvectorEstimationStats

CLIF wrapper for ::kaldi::OnlineIvectorEstimationStats

acc_stats(extractor:IvectorExtractor, feature:VectorBase, gauss_post:list<tuple<int, float>>)

Calls C++ function void ::kaldi::OnlineIvectorEstimationStats::AccStats(::kaldi::IvectorExtractor, ::kaldi::VectorBase<float>, ::std::vector< ::std::pair< ::int32, ::kaldi::BaseFloat> >)

acc_stats_sequence(extractor:IvectorExtractor, features:MatrixBase, gauss_post:list<list<tuple<int, float>>>)

Calls C++ function void ::kaldi::OnlineIvectorEstimationStats::AccStats(::kaldi::IvectorExtractor, ::kaldi::MatrixBase<float>, ::std::vector< ::std::vector< ::std::pair< ::int32, ::kaldi::BaseFloat> > >)

count() → float

Calls C++ function double ::kaldi::OnlineIvectorEstimationStats::Count()

get_ivector(num_cg_iters:int, ivector:DoubleVectorBase)

Gets the current estimate of the iVector.

ivector_dim() → int

Calls C++ function int ::kaldi::OnlineIvectorEstimationStats::IvectorDim()

new_with_other(other:OnlineIvectorEstimationStats) → OnlineIvectorEstimationStats

Calls C++ function std::unique_ptr<::kaldi::OnlineIvectorEstimationStats> ::kaldi::OnlineIvectorEstimationStats::OnlineIvectorEstimationStats(::kaldi::OnlineIvectorEstimationStats)

new_with_params(ivector_dim:int, prior_offset:float, max_count:float) → OnlineIvectorEstimationStats

Calls C++ function std::unique_ptr<::kaldi::OnlineIvectorEstimationStats> ::kaldi::OnlineIvectorEstimationStats::OnlineIvectorEstimationStats(int, float, float)

num_frames() → float

Calls C++ function double ::kaldi::OnlineIvectorEstimationStats::NumFrames()

objf_change(ivector:DoubleVectorBase) → float

Returns the change in objective function per frame from using the default value.

prior_offset() → float

Calls C++ function double ::kaldi::OnlineIvectorEstimationStats::PriorOffset()

read(os:istream, binary:bool)

Calls C++ function void ::kaldi::OnlineIvectorEstimationStats::Read(::std::basic_istream<char, ::std::char_traits<char> >, bool)

scale(scale:float)

Calls C++ function void ::kaldi::OnlineIvectorEstimationStats::Scale(double)

write(os:ostream, binary:bool)

Calls C++ function void ::kaldi::OnlineIvectorEstimationStats::Write(::std::basic_ostream<char, ::std::char_traits<char> >, bool)

class kaldi.ivector.Plda

CLIF wrapper for ::kaldi::Plda

apply_transform(in_transform:DoubleMatrix)

Calls C++ function void ::kaldi::Plda::ApplyTransform(::kaldi::Matrix<double>)

dim() → int

Calls C++ function int ::kaldi::Plda::Dim()

from_other(other:Plda) → Plda

Calls C++ function std::unique_ptr<::kaldi::Plda> ::kaldi::Plda::Plda(::kaldi::Plda)

log_likelihood_ratio(transformed_train_ivector:DoubleVectorBase, num_train_utts:int, transformed_test_ivector:DoubleVectorBase) → float

Calls C++ function double ::kaldi::Plda::LogLikelihoodRatio(::kaldi::VectorBase<double>, int, ::kaldi::VectorBase<double>)

read(os:istream, binary:bool)

Calls C++ function void ::kaldi::Plda::Read(::std::basic_istream<char, ::std::char_traits<char> >, bool)

smooth_within_class_covariance(smoothing_factor:float)

Calls C++ function void ::kaldi::Plda::SmoothWithinClassCovariance(double)

transform_ivector(config:PldaConfig, ivector:DoubleVectorBase, num_examples:int, transformed_ivector:DoubleVectorBase) → float

Calls C++ function double ::kaldi::Plda::TransformIvector(::kaldi::PldaConfig, ::kaldi::VectorBase<double>, int, ::kaldi::VectorBase<double> *)

transform_ivector_single(config:PldaConfig, ivector:VectorBase, num_examples:int, transformed_ivector:VectorBase) → float

Calls C++ function float ::kaldi::Plda::TransformIvector(::kaldi::PldaConfig, ::kaldi::VectorBase<float>, int, ::kaldi::VectorBase<float> *)

write(os:ostream, binary:bool)

Calls C++ function void ::kaldi::Plda::Write(::std::basic_ostream<char, ::std::char_traits<char> >, bool)

class kaldi.ivector.PldaConfig

CLIF wrapper for ::kaldi::PldaConfig

normalize_length

C++ bool PldaConfig.normalize_length

register(opts:OptionsItf)

Calls C++ function void ::kaldi::PldaConfig::Register(::kaldi::OptionsItf *)

simple_length_norm

C++ bool PldaConfig.simple_length_norm

class kaldi.ivector.PldaEstimationConfig

CLIF wrapper for ::kaldi::PldaEstimationConfig

num_em_iters

C++ ::int32 PldaEstimationConfig.num_em_iters

register(opts:OptionsItf)

Calls C++ function void ::kaldi::PldaEstimationConfig::Register(::kaldi::OptionsItf *)

class kaldi.ivector.PldaStats

CLIF wrapper for ::kaldi::PldaStats

add_samples(weight:float, group:DoubleMatrix)

Calls C++ function void ::kaldi::PldaStats::AddSamples(double, ::kaldi::Matrix<double>)

dim() → int

Calls C++ function int ::kaldi::PldaStats::Dim()

init(dim:int)

Calls C++ function void ::kaldi::PldaStats::Init(int)

is_sorted() → bool

Calls C++ function bool ::kaldi::PldaStats::IsSorted()

sort()

Calls C++ function void ::kaldi::PldaStats::Sort()

class kaldi.ivector.PldaUnsupervisedAdaptor

CLIF wrapper for ::kaldi::PldaUnsupervisedAdaptor

add_double_stats(weight:float, ivector:DoubleVector)

Calls C++ function void ::kaldi::PldaUnsupervisedAdaptor::AddStats(double, ::kaldi::Vector<double>)

add_stats(weight:float, ivector:Vector)

Calls C++ function void ::kaldi::PldaUnsupervisedAdaptor::AddStats(double, ::kaldi::Vector<float>)

update_plda(config:PldaUnsupervisedAdaptorConfig, plda:Plda)

Calls C++ function void ::kaldi::PldaUnsupervisedAdaptor::UpdatePlda(::kaldi::PldaUnsupervisedAdaptorConfig, ::kaldi::Plda *)

class kaldi.ivector.PldaUnsupervisedAdaptorConfig

CLIF wrapper for ::kaldi::PldaUnsupervisedAdaptorConfig

between_covar_scale

C++ ::kaldi::BaseFloat PldaUnsupervisedAdaptorConfig.between_covar_scale

mean_diff_scale

C++ ::kaldi::BaseFloat PldaUnsupervisedAdaptorConfig.mean_diff_scale

register(opts:OptionsItf)

Calls C++ function void ::kaldi::PldaUnsupervisedAdaptorConfig::Register(::kaldi::OptionsItf *)

within_covar_scale

C++ ::kaldi::BaseFloat PldaUnsupervisedAdaptorConfig.within_covar_scale

class kaldi.ivector.VadEnergyOptions

CLIF wrapper for ::kaldi::VadEnergyOptions

register(opts:OptionsItf)

Calls C++ function void ::kaldi::VadEnergyOptions::Register(::kaldi::OptionsItf *)

vad_energy_mean_scale

C++ ::kaldi::BaseFloat VadEnergyOptions.vad_energy_mean_scale

vad_energy_threshold

C++ ::kaldi::BaseFloat VadEnergyOptions.vad_energy_threshold

vad_frames_context

C++ ::int32 VadEnergyOptions.vad_frames_context

vad_proportion_threshold

C++ ::kaldi::BaseFloat VadEnergyOptions.vad_proportion_threshold

kaldi.ivector.agglomerative_cluster(costs:Matrix, thresh:float, min_clust:int) → list<int>

Calls C++ function void ::kaldi::AgglomerativeCluster(::kaldi::Matrix<float>, float, int, ::std::vector< ::int32>*)

kaldi.ivector.compute_vad_energy(opts:VadEnergyOptions, input_features:MatrixBase) → Vector

Calls C++ function void ::kaldi::ComputeVadEnergy(::kaldi::VadEnergyOptions, ::kaldi::MatrixBase<float>, ::kaldi::Vector<float>*)

kaldi.ivector.estimate_ivectors_online(feats:Matrix, post:list<list<tuple<int, float>>>, extractor:IvectorExtractor, ivector_period:int, num_cg_iters:int, max_count:float) -> (objf_improvement:float, ivectors:Matrix)

Obtains periodically an estimate of the iVector including all frames up to that point.