TrainableAligner¶
- class aligner.aligner.TrainableAligner(corpus, dictionary, output_directory, beam=100, temp_directory=None, num_jobs=3, call_back=None, mono_params=None, tri_params=None, tri_fmllr_params=None, debug=False, skip_input=False)[source]¶
Aligner that aligns and trains acoustics models on a large dataset
- Parameters:
- corpus
Corpus
Corpus object for the dataset
- dictionary
Dictionary
Dictionary object for the pronunciation dictionary
- output_directorystr
Path to export aligned TextGrids
- temp_directorystr, optional
Specifies the temporary directory root to save files need for Kaldi. If not specified, it will be set to
~/Documents/MFA
- num_jobsint, optional
Number of processes to use, defaults to 3
- call_backcallable, optional
Specifies a call back function for alignment
- mono_params
MonophoneConfig
, optional Monophone training parameters to use, if different from defaults
- tri_params
TriphoneConfig
, optional Triphone training parameters to use, if different from defaults
- tri_fmllr_params
TriphoneFmllrConfig
, optional Speaker-adapted triphone training parameters to use, if different from defaults
- corpus
Attributes
meta
mono_ali_directory
mono_directory
mono_final_model_path
tri_ali_directory
tri_directory
tri_final_model_path
tri_fmllr_ali_directory
tri_fmllr_directory
tri_fmllr_final_model_path
Methods
export_textgrids
()Export a TextGrid file for every sound file in the dataset
get_num_gauss_mono
()Get the number of gaussians for a monophone model
parse_log_directory
(directory, iteration)Parse error files and relate relevant information about unaligned files
save
(path)Output an acoustic model and dictionary to the specified path
setup
()train_mono
()Perform monophone training
train_tri
()Perform triphone training
train_tri_fmllr
()Perform speaker-adapted triphone training