Partitioning speakers (diarization)

This example uses the start-transcription-job. For more information, see StartTranscriptionJob.

aws transcribe start-transcription-job \
--region us-west-2 \
--transcription-job-name my-first-transcription-job \
--media MediaFileUri=s3://DOC-EXAMPLE-BUCKET/my-input-files/my-media-file.flac \
--output-bucket-name DOC-EXAMPLE-BUCKET \
--output-key my-output-files/ \
--language-code en-US \
--show-speaker-labels TRUE \    
--max-speaker-labels 3

Here's another example using the start-transcription-job command, and a request body that enables speaker partitioning with that job.

aws transcribe start-transcription-job \
--region us-west-2 \
--cli-input-json file://my-first-transcription-job.json

The file my-first-transcription-job.json contains the following request body.

{
  "TranscriptionJobName": "my-first-transcription-job",
  "Media": {
        "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/my-input-files/my-media-file.flac"
  },
  "OutputBucketName": "DOC-EXAMPLE-BUCKET",
  "OutputKey": "my-output-files/", 
  "LanguageCode": "en-US",
  "ShowSpeakerLabels": 'TRUE',    
  "MaxSpeakerLabels": 3
 }

This example uses the AWS SDK for Python (Boto3) to identify channels using the start_transcription_job method. For more information, see StartTranscriptionJob.

from __future__ import print_function
import time
import boto3
transcribe = boto3.client('transcribe', 'us-west-2')
job_name = "my-first-transcription-job"
job_uri = "s3://DOC-EXAMPLE-BUCKET/my-input-files/my-media-file.flac"
transcribe.start_transcription_job(
    TranscriptionJobName = job_name,
    Media = {
        'MediaFileUri': job_uri
    },
    OutputBucketName = 'DOC-EXAMPLE-BUCKET',
    OutputKey = 'my-output-files/', 
    LanguageCode = 'en-US', 
    Settings = {
        'ShowSpeakerLabels': True,
        'MaxSpeakerLabels': 3
    }    
)

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

This example creates an HTTP/2 request that partitions speakers in your transcription output. For more information on using HTTP/2 streaming with Amazon Transcribe, see Setting up an HTTP/2 stream. For more detail on parameters and headers specific to Amazon Transcribe, see StartStreamTranscription.

POST /stream-transcription HTTP/2
host: transcribestreaming.us-west-2.amazonaws.com
X-Amz-Target: com.amazonaws.transcribe.Transcribe.StartStreamTranscription
Content-Type: application/vnd.amazon.eventstream
X-Amz-Content-Sha256: string
X-Amz-Date: 20220208T235959Z
Authorization: AWS4-HMAC-SHA256 Credential=access-key/20220208/us-west-2/transcribe/aws4_request, SignedHeaders=content-type;host;x-amz-content-sha256;x-amz-date;x-amz-target;x-amz-security-token, Signature=string
x-amzn-transcribe-language-code: en-US
x-amzn-transcribe-media-encoding: flac
x-amzn-transcribe-sample-rate: 16000             
x-amzn-transcribe-show-speaker-label: true
transfer-encoding: chunked

Parameter definitions can be found in the API Reference; parameters common to all AWS API operations are listed in the Common Parameters section.

This example creates a presigned URL that separates speakers in your transcription output. Line breaks have been added for readability. For more information on using WebSocket streams with Amazon Transcribe, see Setting up a WebSocket stream. For more detail on parameters, see StartStreamTranscription.

GET wss://transcribestreaming.us-west-2.amazonaws.com:8443/stream-transcription-websocket?
&X-Amz-Algorithm=AWS4-HMAC-SHA256
&X-Amz-Credential=AKIAIOSFODNN7EXAMPLE%2F20220208%2Fus-west-2%2Ftranscribe%2Faws4_request
&X-Amz-Date=20220208T235959Z
&X-Amz-Expires=300
&X-Amz-Security-Token=security-token
&X-Amz-Signature=string
&X-Amz-SignedHeaders=content-type%3Bhost%3Bx-amz-date
&language-code=en-US
&specialty=PRIMARYCARE
&type=DICTATION
&media-encoding=flac
&sample-rate=16000        
&show-speaker-label=true

Parameter definitions can be found in the API Reference; parameters common to all AWS API operations are listed in the Common Parameters section.