medkit.audio.transcription.sb_transcriber#

This module needs extra-dependencies not installed as core dependencies of medkit. To install them, use pip install medkit-lib[sb-transcriber].

Classes:

SBTranscriber(model, needs_decoder[, ...])

Transcriber operation based on a SpeechBrain model.
class SBTranscriber(model, needs_decoder, output_label='transcribed_text', add_trailing_dot=True, capitalize=True, cache_dir=None, device=- 1, batch_size=1, uid=None)[source]#

Transcriber operation based on a SpeechBrain model.

For each segment given as input, a transcription attribute will be created with the transcribed text as value. If needed, a text document can later be created from all the transcriptions of a audio document using ~medkit.audio.transcription.TranscribedTextDocument.from_audio_doc

Parameters

  • model (Union[str, Path]) – Name of the model on the Hugging Face models hub, or local path.

  • output_label (str) – Label of the attribute containing the transcribed text that will be attached to the input segments

  • needs_decoder (bool) – Whether the model should be used with the speechbrain EncoderDecoderASR class or the EncoderASR class. If unsure, check the code snippets on the model card on the hub.

  • add_trailing_dot (bool) – If True, a dot will be added at the end of each transcription text.

  • capitalize (bool) – It True, the first letter of each transcription text will be uppercased and the rest lowercased.

  • cache_dir (Union[str, Path, None]) – Directory where to store the downloaded model. If None, speechbrain will use “pretrained_models/” and “model_checkpoints/” directories in the current working directory.

  • device (int) – Device to use for pytorch models. Follows the Hugging Face convention (-1 for cpu and device number for gpu, for instance 0 for “cuda:0”)

  • batch_size (int) – Number of segments in batches processed by the model.

  • uid (str) – Identifier of the transcriber.

Methods:

run(segments)

Add a transcription attribute to each segment with a text value containing the transcribed text.

set_prov_tracer(prov_tracer)

Enable provenance tracing.

Attributes:

description

Contains all the operation init parameters.
run(segments)[source]#

Add a transcription attribute to each segment with a text value containing the transcribed text.

Parameters

segments (List[Segment]) – List of segments to transcribe

property description: medkit.core.operation_desc.OperationDescription#

Contains all the operation init parameters.

Return type

OperationDescription

set_prov_tracer(prov_tracer)#

Enable provenance tracing.

Parameters

prov_tracer (ProvTracer) – The provenance tracer used to trace the provenance.