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MedicalTranscriptionSetting

Used by
Source code in docs_src/capo_transcribe/types/medical_transcription_setting.py 
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class MedicalTranscriptionSetting(TypedDict, closed=True):
    show_speaker_labels: NotRequired["capo_transcribe.types.boolean.Boolean"]
    """<p>Enables speaker partitioning (diarization) in your transcription output. Speaker partitioning labels the speech from individual speakers in your media file.</p> <p>If you enable <code>ShowSpeakerLabels</code> in your request, you must also include <code>MaxSpeakerLabels</code>.</p> <p>For more information, see <a href="https://docs.aws.amazon.com/transcribe/latest/dg/diarization.html">Partitioning speakers (diarization)</a>.</p>"""
    max_speaker_labels: NotRequired["capo_transcribe.types.max_speakers.MaxSpeakers"]
    """<p>Specify the maximum number of speakers you want to partition in your media.</p> <p>Note that if your media contains more speakers than the specified number, multiple speakers are treated as a single speaker.</p> <p>If you specify the <code>MaxSpeakerLabels</code> field, you must set the <code>ShowSpeakerLabels</code> field to true.</p>"""
    channel_identification: NotRequired["capo_transcribe.types.boolean.Boolean"]
    """<p>Enables channel identification in multi-channel audio.</p> <p>Channel identification transcribes the audio on each channel independently, then appends the output for each channel into one transcript.</p> <p>If you have multi-channel audio and do not enable channel identification, your audio is transcribed in a continuous manner and your transcript does not separate the speech by channel.</p> <p>For more information, see <a href="https://docs.aws.amazon.com/transcribe/latest/dg/channel-id.html">Transcribing multi-channel audio</a>.</p>"""
    show_alternatives: NotRequired["capo_transcribe.types.boolean.Boolean"]
    """<p>To include alternative transcriptions within your transcription output, include <code>ShowAlternatives</code> in your transcription request.</p> <p>If you include <code>ShowAlternatives</code>, you must also include <code>MaxAlternatives</code>, which is the maximum number of alternative transcriptions you want Amazon Transcribe Medical to generate.</p> <p>For more information, see <a href="https://docs.aws.amazon.com/transcribe/latest/dg/how-alternatives.html">Alternative transcriptions</a>.</p>"""
    max_alternatives: NotRequired[
        "capo_transcribe.types.max_alternatives.MaxAlternatives"
    ]
    """<p>Indicate the maximum number of alternative transcriptions you want Amazon Transcribe Medical to include in your transcript.</p> <p>If you select a number greater than the number of alternative transcriptions generated by Amazon Transcribe Medical, only the actual number of alternative transcriptions are included.</p> <p>If you include <code>MaxAlternatives</code> in your request, you must also include <code>ShowAlternatives</code> with a value of <code>true</code>.</p> <p>For more information, see <a href="https://docs.aws.amazon.com/transcribe/latest/dg/how-alternatives.html">Alternative transcriptions</a>.</p>"""
    vocabulary_name: NotRequired["capo_transcribe.types.vocabulary_name.VocabularyName"]
    """<p>The name of the custom vocabulary you want to use when processing your medical transcription job. Custom vocabulary names are case sensitive.</p> <p>The language of the specified custom vocabulary must match the language code that you specify in your transcription request. If the languages do not match, the custom vocabulary isn't applied. There are no errors or warnings associated with a language mismatch. US English (<code>en-US</code>) is the only valid language for Amazon Transcribe Medical.</p>"""

channel_identification instance-attribute 

channel_identification: NotRequired[Boolean]

Enables channel identification in multi-channel audio.

Channel identification transcribes the audio on each channel independently, then appends the output for each channel into one transcript.

If you have multi-channel audio and do not enable channel identification, your audio is transcribed in a continuous manner and your transcript does not separate the speech by channel.

For more information, see Transcribing multi-channel audio.

max_alternatives instance-attribute 

max_alternatives: NotRequired[MaxAlternatives]

Indicate the maximum number of alternative transcriptions you want Amazon Transcribe Medical to include in your transcript.

If you select a number greater than the number of alternative transcriptions generated by Amazon Transcribe Medical, only the actual number of alternative transcriptions are included.

If you include MaxAlternatives in your request, you must also include ShowAlternatives with a value of true.

For more information, see Alternative transcriptions.

max_speaker_labels instance-attribute 

max_speaker_labels: NotRequired[MaxSpeakers]

Specify the maximum number of speakers you want to partition in your media.

Note that if your media contains more speakers than the specified number, multiple speakers are treated as a single speaker.

If you specify the MaxSpeakerLabels field, you must set the ShowSpeakerLabels field to true.

show_alternatives instance-attribute 

show_alternatives: NotRequired[Boolean]

To include alternative transcriptions within your transcription output, include ShowAlternatives in your transcription request.

If you include ShowAlternatives, you must also include MaxAlternatives, which is the maximum number of alternative transcriptions you want Amazon Transcribe Medical to generate.

For more information, see Alternative transcriptions.

show_speaker_labels instance-attribute 

show_speaker_labels: NotRequired[Boolean]

Enables speaker partitioning (diarization) in your transcription output. Speaker partitioning labels the speech from individual speakers in your media file.

If you enable ShowSpeakerLabels in your request, you must also include MaxSpeakerLabels.

For more information, see Partitioning speakers (diarization).

vocabulary_name instance-attribute 

vocabulary_name: NotRequired[VocabularyName]

The name of the custom vocabulary you want to use when processing your medical transcription job. Custom vocabulary names are case sensitive.

The language of the specified custom vocabulary must match the language code that you specify in your transcription request. If the languages do not match, the custom vocabulary isn't applied. There are no errors or warnings associated with a language mismatch. US English (en-US) is the only valid language for Amazon Transcribe Medical.