Use StartMedicalTranscriptionJob with an Amazon SDK or CLI

    /// <summary>
    /// Start a medical transcription job for a media file. This method returns
    /// as soon as the job is started.
    /// </summary>
    /// <param name="jobName">A unique name for the medical transcription job.</param>
    /// <param name="mediaFileUri">The URI of the media file, typically an Amazon S3 location.</param>
    /// <param name="mediaFormat">The format of the media file.</param>
    /// <param name="outputBucketName">Location for the output, typically an Amazon S3 location.</param>
    /// <param name="transcriptionType">Conversation or dictation transcription type.</param>
    /// <returns>A MedicalTransactionJob instance with information on the new job.</returns>
    public async Task<MedicalTranscriptionJob> StartMedicalTranscriptionJob(
        string jobName, string mediaFileUri,
        MediaFormat mediaFormat, string outputBucketName, Amazon.TranscribeService.Type transcriptionType)
    {
        var response = await _amazonTranscribeService.StartMedicalTranscriptionJobAsync(
            new StartMedicalTranscriptionJobRequest()
            {
                MedicalTranscriptionJobName = jobName,
                Media = new Media()
                {
                    MediaFileUri = mediaFileUri
                },
                MediaFormat = mediaFormat,
                LanguageCode =
                    LanguageCode
                        .EnUS, // The value must be en-US for medical transcriptions.
                OutputBucketName = outputBucketName,
                OutputKey =
                    jobName, // The value is a key used to fetch the output of the transcription.
                Specialty = Specialty.PRIMARYCARE, // The value PRIMARYCARE must be set.
                Type = transcriptionType
            });
        return response.MedicalTranscriptionJob;
    }

Example 1: To transcribe a medical dictation stored as an audio file

The following start-medical-transcription-job example transcribes an audio file. You specify the location of the transcription output in the OutputBucketName parameter.

aws transcribe start-medical-transcription-job \
    --cli-input-json file://myfile.json

Contents of myfile.json:

{
    "MedicalTranscriptionJobName": "simple-dictation-medical-transcription-job",
    "LanguageCode": "language-code",
    "Specialty": "PRIMARYCARE",
    "Type": "DICTATION",
    "OutputBucketName":"amzn-s3-demo-bucket",
    "Media": {
        "MediaFileUri": "s3://amzn-s3-demo-bucket/your-audio-file.extension"
    }
}

Output:

{
    "MedicalTranscriptionJob": {
        "MedicalTranscriptionJobName": "simple-dictation-medical-transcription-job",
        "TranscriptionJobStatus": "IN_PROGRESS",
        "LanguageCode": "language-code",
        "Media": {
            "MediaFileUri": "s3://amzn-s3-demo-bucket/your-audio-file.extension"
        },
        "StartTime": "2020-09-20T00:35:22.256000+00:00",
        "CreationTime": "2020-09-20T00:35:22.218000+00:00",
        "Specialty": "PRIMARYCARE",
        "Type": "DICTATION"
    }
}

For more information, see Batch Transcription Overview in the Amazon Transcribe Developer Guide.

Example 2: To transcribe a clinician-patient dialogue stored as an audio file

The following start-medical-transcription-job example transcribes an audio file containing a clinician-patient dialogue. You specify the location of the transcription output in the OutputBucketName parameter.

aws transcribe start-medical-transcription-job \
    --cli-input-json file://mysecondfile.json

Contents of mysecondfile.json:

{
    "MedicalTranscriptionJobName": "simple-dictation-medical-transcription-job",
    "LanguageCode": "language-code",
    "Specialty": "PRIMARYCARE",
    "Type": "CONVERSATION",
    "OutputBucketName":"amzn-s3-demo-bucket",
    "Media": {
        "MediaFileUri": "s3://amzn-s3-demo-bucket/your-audio-file.extension"
    }
}

Output:

{
    "MedicalTranscriptionJob": {
        "MedicalTranscriptionJobName": "simple-conversation-medical-transcription-job",
        "TranscriptionJobStatus": "IN_PROGRESS",
        "LanguageCode": "language-code",
        "Media": {
            "MediaFileUri": "s3://amzn-s3-demo-bucket/your-audio-file.extension"
        },
        "StartTime": "2020-09-20T23:19:49.965000+00:00",
        "CreationTime": "2020-09-20T23:19:49.941000+00:00",
        "Specialty": "PRIMARYCARE",
        "Type": "CONVERSATION"
    }
}

For more information, see Batch Transcription Overview in the Amazon Transcribe Developer Guide.

Example 3: To transcribe a multichannel audio file of a clinician-patient dialogue

The following start-medical-transcription-job example transcribes the audio from each channel in the audio file and merges the separate transcriptions from each channel into a single transcription output. You specify the location of the transcription output in the OutputBucketName parameter.

aws transcribe start-medical-transcription-job \
    --cli-input-json file://mythirdfile.json

Contents of mythirdfile.json:

{
    "MedicalTranscriptionJobName": "multichannel-conversation-medical-transcription-job",
    "LanguageCode": "language-code",
    "Specialty": "PRIMARYCARE",
    "Type": "CONVERSATION",
    "OutputBucketName":"amzn-s3-demo-bucket",
        "Media": {
          "MediaFileUri": "s3://amzn-s3-demo-bucket/your-audio-file.extension"
        },
        "Settings":{
          "ChannelIdentification": true
        }
}

Output:

{
    "MedicalTranscriptionJob": {
        "MedicalTranscriptionJobName": "multichannel-conversation-medical-transcription-job",
        "TranscriptionJobStatus": "IN_PROGRESS",
        "LanguageCode": "language-code",
        "Media": {
            "MediaFileUri": "s3://amzn-s3-demo-bucket/your-audio-file.extension"
        },
        "StartTime": "2020-09-20T23:46:44.081000+00:00",
        "CreationTime": "2020-09-20T23:46:44.053000+00:00",
        "Settings": {
            "ChannelIdentification": true
        },
        "Specialty": "PRIMARYCARE",
        "Type": "CONVERSATION"
    }
}

For more information, see Channel Identification in the Amazon Transcribe Developer Guide.

Example 4: To transcribe an audio file of a clinician-patient dialogue and identify the speakers in the transcription output

The following start-medical-transcription-job example transcribes an audio file and labels the speech of each speaker in the transcription output. You specify the location of the transcription output in the OutputBucketName parameter.

aws transcribe start-medical-transcription-job \
    --cli-input-json file://myfourthfile.json

Contents of myfourthfile.json:

{
    "MedicalTranscriptionJobName": "speaker-id-conversation-medical-transcription-job",
    "LanguageCode": "language-code",
    "Specialty": "PRIMARYCARE",
    "Type": "CONVERSATION",
    "OutputBucketName":"amzn-s3-demo-bucket",
    "Media": {
        "MediaFileUri": "s3://amzn-s3-demo-bucket/your-audio-file.extension"
        },
    "Settings":{
        "ShowSpeakerLabels": true,
        "MaxSpeakerLabels": 2
        }
}

Output:

{
    "MedicalTranscriptionJob": {
        "MedicalTranscriptionJobName": "speaker-id-conversation-medical-transcription-job",
        "TranscriptionJobStatus": "IN_PROGRESS",
        "LanguageCode": "language-code",
        "Media": {
            "MediaFileUri": "s3://amzn-s3-demo-bucket/your-audio-file.extension"
        },
        "StartTime": "2020-09-21T18:43:37.265000+00:00",
        "CreationTime": "2020-09-21T18:43:37.157000+00:00",
        "Settings": {
            "ShowSpeakerLabels": true,
            "MaxSpeakerLabels": 2
        },
        "Specialty": "PRIMARYCARE",
        "Type": "CONVERSATION"
    }
}

For more information, see Identifying Speakers in the Amazon Transcribe Developer Guide.

Example 5: To transcribe a medical conversation stored as an audio file with up to two transcription alternatives

The following start-medical-transcription-job example creates up to two alternative transcriptions from a single audio file. Every transcriptions has a level of confidence associated with it. By default, Amazon Transcribe returns the transcription with the highest confidence level. You can specify that Amazon Transcribe return additional transcriptions with lower confidence levels. You specify the location of the transcription output in the OutputBucketName parameter.

aws transcribe start-medical-transcription-job \
    --cli-input-json file://myfifthfile.json

Contents of myfifthfile.json:

{
    "MedicalTranscriptionJobName": "alternatives-conversation-medical-transcription-job",
    "LanguageCode": "language-code",
    "Specialty": "PRIMARYCARE",
    "Type": "CONVERSATION",
    "OutputBucketName":"amzn-s3-demo-bucket",
    "Media": {
        "MediaFileUri": "s3://amzn-s3-demo-bucket/your-audio-file.extension"
    },
    "Settings":{
        "ShowAlternatives": true,
        "MaxAlternatives": 2
    }
}

Output:

{
    "MedicalTranscriptionJob": {
        "MedicalTranscriptionJobName": "alternatives-conversation-medical-transcription-job",
        "TranscriptionJobStatus": "IN_PROGRESS",
        "LanguageCode": "language-code",
        "Media": {
            "MediaFileUri": "s3://amzn-s3-demo-bucket/your-audio-file.extension"
        },
        "StartTime": "2020-09-21T19:09:18.199000+00:00",
        "CreationTime": "2020-09-21T19:09:18.171000+00:00",
        "Settings": {
            "ShowAlternatives": true,
            "MaxAlternatives": 2
        },
        "Specialty": "PRIMARYCARE",
        "Type": "CONVERSATION"
    }
}

For more information, see Alternative Transcriptions in the Amazon Transcribe Developer Guide.

Example 6: To transcribe an audio file of a medical dictation with up to two alternative transcriptions

The following start-medical-transcription-job example transcribes an audio file and uses a vocabulary filter to mask any unwanted words. You specify the location of the transcription output in the OutputBucketName parameter.

aws transcribe start-medical-transcription-job \
    --cli-input-json file://mysixthfile.json

Contents of mysixthfile.json:

{
    "MedicalTranscriptionJobName": "alternatives-conversation-medical-transcription-job",
    "LanguageCode": "language-code",
    "Specialty": "PRIMARYCARE",
    "Type": "DICTATION",
    "OutputBucketName":"amzn-s3-demo-bucket",
    "Media": {
        "MediaFileUri": "s3://amzn-s3-demo-bucket/your-audio-file.extension"
    },
    "Settings":{
          "ShowAlternatives": true,
          "MaxAlternatives": 2
    }
}

Output:

{
    "MedicalTranscriptionJob": {
        "MedicalTranscriptionJobName": "alternatives-dictation-medical-transcription-job",
        "TranscriptionJobStatus": "IN_PROGRESS",
        "LanguageCode": "language-code",
        "Media": {
            "MediaFileUri": "s3://amzn-s3-demo-bucket/your-audio-file.extension"
        },
        "StartTime": "2020-09-21T21:01:14.592000+00:00",
        "CreationTime": "2020-09-21T21:01:14.569000+00:00",
        "Settings": {
            "ShowAlternatives": true,
            "MaxAlternatives": 2
        },
        "Specialty": "PRIMARYCARE",
        "Type": "DICTATION"
    }
}

For more information, see Alternative Transcriptions in the Amazon Transcribe Developer Guide.

Example 7: To transcribe an audio file of a medical dictation with increased accuracy by using a custom vocabulary

The following start-medical-transcription-job example transcribes an audio file and uses a medical custom vocabulary you've previously created to increase the transcription accuracy. You specify the location of the transcription output in the OutputBucketName parameter.

aws transcribe start-transcription-job \
    --cli-input-json file://myseventhfile.json

Contents of mysixthfile.json:

{
    "MedicalTranscriptionJobName": "vocabulary-dictation-medical-transcription-job",
    "LanguageCode": "language-code",
    "Specialty": "PRIMARYCARE",
    "Type": "DICTATION",
    "OutputBucketName":"amzn-s3-demo-bucket",
    "Media": {
        "MediaFileUri": "s3://amzn-s3-demo-bucket/your-audio-file.extension"
    },
    "Settings":{
        "VocabularyName": "cli-medical-vocab-1"
    }
}

Output:

{
    "MedicalTranscriptionJob": {
        "MedicalTranscriptionJobName": "vocabulary-dictation-medical-transcription-job",
        "TranscriptionJobStatus": "IN_PROGRESS",
        "LanguageCode": "language-code",
        "Media": {
            "MediaFileUri": "s3://amzn-s3-demo-bucket/your-audio-file.extension"
        },
        "StartTime": "2020-09-21T21:17:27.045000+00:00",
        "CreationTime": "2020-09-21T21:17:27.016000+00:00",
        "Settings": {
            "VocabularyName": "cli-medical-vocab-1"
        },
        "Specialty": "PRIMARYCARE",
        "Type": "DICTATION"
    }
}

For more information, see Medical Custom Vocabularies in the Amazon Transcribe Developer Guide.

Create the client.

import { TranscribeClient } from "@aws-sdk/client-transcribe";
// Set the AWS Region.
const REGION = "REGION"; //e.g. "us-east-1"
// Create an Amazon Transcribe service client object.
const transcribeClient = new TranscribeClient({ region: REGION });
export { transcribeClient };

Start a medical transcription job.

// Import the required AWS SDK clients and commands for Node.js
import { StartMedicalTranscriptionJobCommand } from "@aws-sdk/client-transcribe";
import { transcribeClient } from "./libs/transcribeClient.js";

// Set the parameters
export const params = {
  MedicalTranscriptionJobName: "MEDICAL_JOB_NAME", // Required
  OutputBucketName: "OUTPUT_BUCKET_NAME", // Required
  Specialty: "PRIMARYCARE", // Required. Possible values are 'PRIMARYCARE'
  Type: "JOB_TYPE", // Required. Possible values are 'CONVERSATION' and 'DICTATION'
  LanguageCode: "LANGUAGE_CODE", // For example, 'en-US'
  MediaFormat: "SOURCE_FILE_FORMAT", // For example, 'wav'
  Media: {
    MediaFileUri: "SOURCE_FILE_LOCATION",
    // The S3 object location of the input media file. The URI must be in the same region
    // as the API endpoint that you are calling.For example,
    // "https://transcribe-demo.s3-REGION.amazonaws.com/hello_world.wav"
  },
};

export const run = async () => {
  try {
    const data = await transcribeClient.send(
      new StartMedicalTranscriptionJobCommand(params),
    );
    console.log("Success - put", data);
    return data; // For unit tests.
  } catch (err) {
    console.log("Error", err);
  }
};
run();