TranscriberMixin#
- class montreal_forced_aligner.transcription.transcriber.TranscriberMixin(transition_scale=1.0, acoustic_scale=0.083333, self_loop_scale=0.1, beam=10, silence_weight=0.0, first_beam=10, first_max_active=2000, language_model_weight=10, word_insertion_penalty=0.5, **kwargs)[source]#
Bases:
CorpusAligner
,TranscriptionEvaluationMixin
Abstract class for MFA transcribers
- 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
beam (int) – Size of the beam to use in decoding, defaults to 10
silence_weight (float) – Weight on silence in fMLLR estimation
max_active (int) – Max active for decoding
lattice_beam (int) – Beam width for decoding lattices
first_beam (int) – Beam for decoding in initial speaker-independent pass, only used if
uses_speaker_adaptation
is truefirst_max_active (int) – Max active for decoding in initial speaker-independent pass, only used if
uses_speaker_adaptation
is truelanguage_model_weight (float) – Weight of language model
word_insertion_penalty (float) – Penalty for inserting words
- calc_final_fmllr()[source]#
Calculate final fMLLR transforms
See also
FinalFmllrFunction
Multiprocessing function
TranscriberMixin.final_fmllr_arguments
Arguments for function
- calc_initial_fmllr()[source]#
Calculate initial fMLLR transforms
See also
InitialFmllrFunction
Multiprocessing function
TranscriberMixin.initial_fmllr_arguments
Arguments for function
- carpa_lm_rescore()[source]#
Rescore lattices with CARPA language model
See also
CarpaLmRescoreFunction
Multiprocessing function
TranscriberMixin.carpa_lm_rescore_arguments
Arguments for function
- carpa_lm_rescore_arguments()[source]#
Generate Job arguments for
CarpaLmRescoreFunction
- Returns:
Arguments for processing
- Return type:
list[
CarpaLmRescoreArguments
]
- decode()[source]#
Generate lattices
See also
DecodeFunction
Multiprocessing function
TranscriberMixin.decode_arguments
Arguments for function
- decode_arguments(workflow=WorkflowType.transcription)[source]#
Generate Job arguments for
DecodeFunction
- Returns:
Arguments for processing
- Return type:
list[
DecodeArguments
]
- final_fmllr_arguments()[source]#
Generate Job arguments for
FinalFmllrFunction
- Returns:
Arguments for processing
- Return type:
list[
FinalFmllrArguments
]
- fmllr_rescore()[source]#
Rescore lattices with final fMLLR transforms
See also
FmllrRescoreFunction
Multiprocessing function
TranscriberMixin.fmllr_rescore_arguments
Arguments for function
- fmllr_rescore_arguments()[source]#
Generate Job arguments for
FmllrRescoreFunction
- Returns:
Arguments for processing
- Return type:
list[
FmllrRescoreArguments
]
- initial_fmllr_arguments()[source]#
Generate Job arguments for
InitialFmllrFunction
- Returns:
Arguments for processing
- Return type:
list[
InitialFmllrArguments
]
- lm_rescore()[source]#
Rescore lattices with bigger language model
See also
LmRescoreFunction
Multiprocessing function
TranscriberMixin.lm_rescore_arguments
Arguments for function
- lm_rescore_arguments()[source]#
Generate Job arguments for
LmRescoreFunction
- Returns:
Arguments for processing
- Return type:
list[
LmRescoreArguments
]
- property lm_rescore_options#
Options needed for rescoring the language model
- property model_directory#
Model directory for the transcriber
- property model_log_directory#
Model directory for the transcriber
- train_speaker_lm_arguments()[source]#
Generate Job arguments for
TrainSpeakerLmFunction
- Returns:
Arguments for processing
- Return type:
list[
TrainSpeakerLmArguments
]
- transcribe_fmllr()[source]#
Run fMLLR estimation over initial decoding lattices and rescore
See also
InitialFmllrFunction
Multiprocessing helper function for each job
LatGenFmllrFunction
Multiprocessing helper function for each job
FinalFmllrFunction
Multiprocessing helper function for each job
FmllrRescoreFunction
Multiprocessing helper function for each job
LmRescoreFunction
Multiprocessing helper function for each job
CarpaLmRescoreFunction
Multiprocessing helper function for each job
- property transcribe_fmllr_options#
Options needed for calculating fMLLR transformations
- transcribe_utterances()[source]#
Transcribe the corpus
See also
DecodeFunction
Multiprocessing helper function for each job
LmRescoreFunction
Multiprocessing helper function for each job
CarpaLmRescoreFunction
Multiprocessing helper function for each job
- Raises:
KaldiProcessingError – If there were any errors in running Kaldi binaries