segment_utterance_transcript

montreal_forced_aligner.vad.multiprocessing.segment_utterance_transcript(acoustic_model, utterance, lexicon_compiler, vad_model, segmentation_options, cmvn=None, fmllr_trans=None, mfcc_options=None, vad_options=None, g2p_model=None, interjection_words=None, acoustic_scale=0.1, beam=16.0, lattice_beam=10.0, max_active=7000, min_active=200, prune_interval=25, beam_delta=0.5, hash_ratio=2.0, prune_scale=0.1, boost_silence=1.0)

Split an utterance and its transcript into multiple transcribed utterances

Parameters:

• acoustic_model (AcousticModel) – Acoustic model to use in splitting transcriptions

• utterance (Utterance) – Utterance to split

• lexicon_compiler (LexiconCompiler) – Lexicon compiler

• vad_model (VAD or None) – VAD model from SpeechBrain, if None, then Kaldi’s energy-based VAD is used

• segmentation_options (dict[str, Any]) – Segmentation options

• cmvn (DoubleMatrix) – CMVN stats to apply

• fmllr_trans (FloatMatrix) – fMLLR transformation matrix for speaker adaptation

• mfcc_options (dict[str, Any], optional) – MFCC options for energy based VAD

• vad_options (dict[str, Any], optional) – Options for energy based VAD

• acoustic_scale (float, optional) – Defaults to 0.1

• beam (float, optional) – Defaults to 16

• lattice_beam (float, optional) – Defaults to 10

• max_active (int, optional) – Defaults to 7000

• min_active (int, optional) – Defaults to 250

• prune_interval (int, optional) – Defaults to 25

• beam_delta (float, optional) – Defaults to 0.5

• hash_ratio (float, optional) – Defaults to 2.0

• prune_scale (float, optional) – Defaults to 0.1

• boost_silence (float, optional) – Defaults to 1.0

Returns:

Split utterances

Return type:

list[Utterance]