LdaTrainer

class montreal_forced_aligner.trainers.LdaTrainer(default_feature_config)[source]

Configuration class for LDA+MLLT training

Attributes:
lda_dimension : int

Dimensionality of the LDA matrix

mllt_iterations : list

List of iterations to perform MLLT estimation

random_prune : float

This is approximately the ratio by which we will speed up the LDA and MLLT calculations via randomized pruning

Attributes

align_directory
align_log_directory
align_options
feature_file_base_name
final_gaussian_iteration
gaussian_increment
lda_options
log_directory
meta
phone_type
train_directory
train_type

Methods

align(subset[, call_back])
compute_calculated_properties()
export_textgrids() Export a TextGrid file for every sound file in the dataset
get_unaligned_utterances()
init_training(identifier, …)
parse_log_directory(directory, iteration, …) Parse error files and relate relevant information about unaligned files
save(path[, root_directory]) Output an acoustic model and dictionary to the specified path
train([call_back])
update(data)