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:
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
- 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
- property train_type#
Training identifier