AlignMixin#

class montreal_forced_aligner.alignment.mixins.AlignMixin(transition_scale=1.0, acoustic_scale=0.1, self_loop_scale=0.1, boost_silence=1.0, beam=10, retry_beam=40, fine_tune=False, phone_confidence=False, use_phone_model=False, **kwargs)[source]#

Bases: DictionaryMixin

Configuration object for alignment

Parameters:
  • transition_scale (float) – Transition scale, defaults to 1.0

  • acoustic_scale (float) – Acoustic scale, defaults to 0.1

  • self_loop_scale (float) – Self-loop scale, defaults to 0.1

  • boost_silence (float) – Factor to boost silence probabilities, 1.0 is no boost or reduction

  • beam (int) – Size of the beam to use in decoding, defaults to 10

  • retry_beam (int) – Size of the beam to use in decoding if it fails with the initial beam width, defaults to 40

See also

DictionaryMixin

For dictionary parsing parameters

Variables:

jobs (list[Job]) – Jobs to process

align_arguments()[source]#

Generate Job arguments for AlignFunction

Returns:

Arguments for processing

Return type:

list[AlignArguments]

property align_options#

Options for use in aligning

align_utterances(training=False)[source]#

Multiprocessing function that aligns based on the current model.

See also

AlignFunction

Multiprocessing helper function for each job

AlignMixin.align_arguments

Job method for generating arguments for the helper function

align_si.sh

Reference Kaldi script

align_fmllr.sh

Reference Kaldi script

alignment_configuration()[source]#

Configuration parameters

property alignment_model_path#

Acoustic model file path for speaker-independent alignment

compile_train_graphs()[source]#

Multiprocessing function that compiles training graphs for utterances.

See also

CompileTrainGraphsFunction

Multiprocessing helper function for each job

AlignMixin.compile_train_graphs_arguments

Job method for generating arguments for the helper function

align_si.sh

Reference Kaldi script

align_fmllr.sh

Reference Kaldi script

compile_train_graphs_arguments()[source]#

Generate Job arguments for CompileTrainGraphsFunction

Returns:

Arguments for processing

Return type:

list[CompileTrainGraphsArguments]

abstract property data_directory#

Corpus data directory

property model_path#

Acoustic model file path

property num_current_utterances#

Number of current utterances

phone_confidence_arguments()[source]#

Generate Job arguments for PhoneConfidenceFunction

Returns:

Arguments for processing

Return type:

list[PhoneConfidenceArguments]

property phone_pdf_counts_path#

Acoustic model file path

property tree_path#

Path to tree file

abstract property working_directory#

Working directory

abstract property working_log_directory#

Working log directory