# Transcribing an audio file using a medical custom vocabulary
<a name="start-med-custom-vocab-job"></a>

Use the [https://docs.aws.amazon.com/transcribe/latest/APIReference/API_StartMedicalTranscriptionJob.html](https://docs.aws.amazon.com/transcribe/latest/APIReference/API_StartMedicalTranscriptionJob.html) or the AWS Management Console to start a transcription job that uses a custom vocabulary to improve transcription accuracy.

## AWS Management Console
<a name="start-med-custom-vocab-job-console"></a>

1. Sign in to the [AWS Management Console](https://console.aws.amazon.com/transcribe/).

1. In the navigation pane, under Amazon Transcribe Medical, choose **Transcription jobs**.

1. Choose **Create job**.

1. On the **Specify job details** page, provide information about your transcription job.

1. Choose **Next**.

1. Under **Customization**, enable **Custom vocabulary**.

1. Under **Vocabulary selection**, choose a custom vocabulary.

1. Choose **Create**.

## API
<a name="start-med-custom-vocab-api"></a>

**To enable speaker partitioning in an audio file using a batch transcription job (API)**
+ For the [https://docs.aws.amazon.com/transcribe/latest/APIReference/API_StartMedicalTranscriptionJob.html](https://docs.aws.amazon.com/transcribe/latest/APIReference/API_StartMedicalTranscriptionJob.html) API, specify the following.

  1. For `MedicalTranscriptionJobName`, specify a name that is unique in your AWS account.

  1. For `LanguageCode`, specify the language code that corresponds to the language spoken in your audio file and the language of your vocabulary filter.

  1. For the `MediaFileUri` parameter of the `Media` object, specify the name of the audio file that you want to transcribe.

  1. For `Specialty`, specify the medical specialty of the clinician speaking in the audio file.

  1. For `Type`, specify whether the audio file is a conversation or a dictation.

  1. For `OutputBucketName`, specify the Amazon S3 bucket to store the transcription results.

  1. For the `Settings` object, specify the following.

     1. `VocabularyName` – the name of your custom vocabulary.

The following request uses the AWS SDK for Python (Boto3) to start a batch transcription job with a custom vocabulary.

```
from __future__ import print_function
import time
import boto3
transcribe = boto3.client('transcribe', 'us-west-2')
job_name = "my-first-med-transcription-job"
job_uri = "s3://amzn-s3-demo-bucket/my-input-files/my-media-file.flac"
transcribe.start_medical_transcription_job(
   MedicalTranscriptionJobName = job_name,
   Media = {
       'MediaFileUri': job_uri
   },
   OutputBucketName = 'amzn-s3-demo-bucket',
   OutputKey = 'my-output-files/', 
   LanguageCode = 'en-US',
   Specialty = 'PRIMARYCARE',
   Type = 'CONVERSATION',
   Settings = {
       'VocabularyName': 'example-med-custom-vocab'
       }
 )

while True:
   status = transcribe.get_medical_transcription_job(MedicalTranscriptionJobName = job_name)
   if status['MedicalTranscriptionJob']['TranscriptionJobStatus'] in ['COMPLETED', 'FAILED']:
        break
    print("Not ready yet...")
    time.sleep(5)
print(status)
```