MonophoneTrainer#
- class montreal_forced_aligner.acoustic_modeling.MonophoneTrainer(subset=2000, initial_gaussians=135, initial_beam=6, max_gaussians=1000, power=0.25, boost_silence=1.25, **kwargs)[source]#
Bases:
AcousticModelTrainingMixin
Configuration class for monophone training
- Variables:
subset (int) – Number of utterances to use, defaults to 2000
initial_gaussians (int) – Number of gaussians to begin training, defaults to 135
max_gaussians (int) – Total number of gaussians, defaults to 1000
power (float) – Exponent for number of gaussians according to occurrence counts, defaults to 0.25
See also
AcousticModelTrainingMixin
For acoustic model training parsing parameters
- property align_options#
Alignment parameters
- compute_calculated_properties()[source]#
Generate realignment iterations and initial gaussians based on configuration
- mono_align_equal()[source]#
Multiprocessing function that creates equal alignments for base monophone training.
See also
MonoAlignEqualFunction
Multiprocessing helper function for each job
MonophoneTrainer.mono_align_equal_arguments
Job method for generating arguments for the helper function
- gmmbin/gmm-sum-accs.cc
Relevant Kaldi binary
- gmmbin/gmm-est.cc
Relevant Kaldi binary
- train_mono.sh
Reference Kaldi script
- mono_align_equal_arguments()[source]#
Generate Job arguments for
MonoAlignEqualFunction
- Returns:
Arguments for processing
- Return type:
list[
MonoAlignEqualArguments
]
- property phone_type#
Phone type
- property train_type#
Training identifier