IvectorTrainer#

class montreal_forced_aligner.ivector.trainer.IvectorTrainer(num_iterations=10, subsample=5, gaussian_min_count=100, **kwargs)[source]#

Bases: IvectorModelTrainingMixin, IvectorConfigMixin

Trainer for a block of ivector extractor training

Parameters:
  • num_iterations (int) – Number of iterations, defaults to 10

  • subsample (int) – Subsample factor for feature frames, defaults to 5

  • gaussian_min_count (int) –

See also

IvectorModelTrainingMixin

For base parameters for ivector training

IvectorConfigMixin

For parameters for ivector feature generation

acc_ivector_stats()[source]#

Multiprocessing function that accumulates ivector extraction stats.

See also

AccIvectorStatsFunction

Multiprocessing helper function for each job

IvectorTrainer.acc_ivector_stats_arguments

Job method for generating arguments for the helper function

ivectorbin/ivector-extractor-sum-accs.cc

Relevant Kaldi binary

ivectorbin/ivector-extractor-est.cc

Relevant Kaldi binary

sid/train_ivector_extractor.sh

Reference Kaldi script

acc_ivector_stats_arguments()[source]#

Generate Job arguments for AccIvectorStatsFunction

Returns:

Arguments for processing

Return type:

list[AccIvectorStatsArguments]

property dubm_path#

DUBM model path

property exported_model_path#

Temporary directory path that trainer will save ivector extractor model

finalize_training()[source]#

Finalize ivector extractor training

gauss_to_post()[source]#

Multiprocessing function that does Gaussian selection and posterior extraction

See also

GaussToPostFunction

Multiprocessing helper function for each job

IvectorTrainer.gauss_to_post_arguments

Job method for generating arguments for the helper function

sid/train_ivector_extractor.sh

Reference Kaldi script

gauss_to_post_arguments()[source]#

Generate Job arguments for GaussToPostFunction

Returns:

Arguments for processing

Return type:

list[GaussToPostArguments]

property ie_path#

Current ivector extractor model path

property ivector_options#

Options for ivector training and extracting

property meta#

Metadata information for ivector extractor models

property next_ie_path#

Next iteration’s ivector extractor model path

train_iteration()[source]#

Run an iteration of training

property train_type#

Training identifier