# Partitioning speakers (diarization) With speaker diarization, you can distinguish between different speakers in your transcription output. Amazon Transcribe can differentiate between a maximum of 30 unique speakers and labels the text from each unique speaker with a unique value (`spk_0` through `spk_9`). In addition to the [standard transcript sections](how-input.md#how-it-works-output) (`transcripts` and `items`), requests with speaker partitioning enabled include a `speaker_labels` section. This section is grouped by speaker and contains information on each utterance, including speaker label and timestamps. ``` "speaker_labels": { "channel_label": "ch_0", "speakers": 2, "segments": [ { "start_time": "4.87", "speaker_label": "spk_0", "end_time": "6.88", "items": [ { "start_time": "4.87", "speaker_label": "spk_0", "end_time": "5.02" }, {{...}} { "start_time": "8.49", "speaker_label": "spk_1", "end_time": "9.24", "items": [ { "start_time": "8.49", "speaker_label": "spk_1", "end_time": "8.88" }, ``` To view a complete example transcript with speaker partitioning (for two speakers), see [Example diarization output (batch)](diarization-output-batch.md). ## Partitioning speakers in a batch transcription To partition speakers in a batch transcription, see the following examples: ### AWS Management Console 1. Sign in to the [AWS Management Console](https://console.aws.amazon.com/transcribe/). 1. In the navigation pane, choose **Transcription jobs**, then select **Create job** (top right). This opens the **Specify job details** page. ![Amazon Transcribe console 'Specify job details' page. In the 'Job settings' panel, you can specify a name for your transcription job, select a Model type, and specify your language settings.](http://docs.aws.amazon.com/transcribe/latest/dg/images/console-batch-job-details-1.png) 1. Fill in any fields you want to include on the **Specify job details** page, then select **Next**. This takes you to the **Configure job - *optional*** page. To enable speaker partitioning, in **Audio settings**, choose **Audio identification**. Then choose **Speaker partitioning** and specify the number of speakers. ![Amazon Transcribe console 'Configure job' page. In the 'Audio settings' panel, you can enable 'Speaker partitioning'.](http://docs.aws.amazon.com/transcribe/latest/dg/images/diarization-batch.png) 1. Select **Create job** to run your transcription job. ### AWS CLI This example uses the [start-transcription-job](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/transcribe/start-transcription-job.html). For more information, see [https://docs.aws.amazon.com/transcribe/latest/APIReference/API_StartTranscriptionJob.html](https://docs.aws.amazon.com/transcribe/latest/APIReference/API_StartTranscriptionJob.html). ``` aws transcribe start-transcription-job \ --region {{us-west-2}} \ --transcription-job-name {{my-first-transcription-job}} \ --media MediaFileUri=s3://{{amzn-s3-demo-bucket}}/{{my-input-files}}/{{my-media-file}}.{{flac}} \ --output-bucket-name {{amzn-s3-demo-bucket}} \ --output-key {{my-output-files}}/ \ --language-code {{en-US}} \ --settings ShowSpeakerLabels={{true}},MaxSpeakerLabels={{3}} ``` Here's another example using the [start-transcription-job](https://awscli.amazonaws.com/v2/documentation/api/latest/reference/transcribe/start-transcription-job.html) 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://{{amzn-s3-demo-bucket}}/{{my-input-files}}/{{my-media-file}}.{{flac}}" }, "OutputBucketName": "{{amzn-s3-demo-bucket}}", "OutputKey": "{{my-output-files}}/", "LanguageCode": "{{en-US}}", "ShowSpeakerLabels": 'TRUE', "MaxSpeakerLabels": {{3}} } ``` ### AWS SDK for Python (Boto3) This example uses the AWS SDK for Python (Boto3) to identify channels using the [start\_transcription\_job](https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/transcribe.html#TranscribeService.Client.start_transcription_job) method. For more information, see [StartTranscriptionJob](https://docs.aws.amazon.com/transcribe/latest/APIReference/API_StartTranscriptionJob.html). ``` 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://{{amzn-s3-demo-bucket}}/{{my-input-files}}/{{my-media-file}}.{{flac}}" transcribe.start_transcription_job( TranscriptionJobName = job_name, Media = { 'MediaFileUri': job_uri }, OutputBucketName = '{{amzn-s3-demo-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) ``` ## Partitioning speakers in a streaming transcription To partition speakers in a streaming transcription, see the following examples: ### Streaming transcriptions 1. Sign in to the [AWS Management Console](https://console.aws.amazon.com/transcribe/). 1. In the navigation pane, choose **Real-time transcription**. Scroll down to **Audio settings** and expand this field if it is minimized. ![Amazon Transcribe console screenshot: the 'audio settings' tab on the 'real-time transcription' page.](http://docs.aws.amazon.com/transcribe/latest/dg/images/diarization-streaming1.png) 1. Toggle on **Speaker partitioning**. ![Amazon Transcribe console screenshot: the expanded 'audio settings' tab with speaker partitioning enabled.](http://docs.aws.amazon.com/transcribe/latest/dg/images/diarization-streaming2.png) 1. You're now ready to transcribe your stream. Select **Start streaming** and begin speaking. To end your dictation, select **Stop streaming**. ### HTTP/2 stream 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](streaming-setting-up.md#streaming-http2). For more detail on parameters and headers specific to Amazon Transcribe, see [StartStreamTranscription](https://docs.aws.amazon.com/transcribe/latest/APIReference/API_streaming_StartStreamTranscription.html). ``` 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: {{20220208}}T{{235959}}Z 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](https://docs.aws.amazon.com/transcribe/latest/APIReference/API_Reference.html); parameters common to all AWS API operations are listed in the [Common Parameters](https://docs.aws.amazon.com/transcribe/latest/APIReference/CommonParameters.html) section. ### WebSocket stream 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](streaming-setting-up.md#streaming-websocket). For more detail on parameters, see [https://docs.aws.amazon.com/transcribe/latest/APIReference/API_streaming_StartStreamTranscription.html](https://docs.aws.amazon.com/transcribe/latest/APIReference/API_streaming_StartStreamTranscription.html). ``` GET wss://transcribestreaming.{{us-west-2}}.amazonaws.com:8443/stream-transcription-websocket? &X-Amz-Algorithm=AWS4-HMAC-SHA256 &X-Amz-Credential={{AKIAIOSFODNN7EXAMPLE}}%2F{{20220208}}%2F{{us-west-2}}%2F{{transcribe}}%2Faws4_request &X-Amz-Date={{20220208}}T{{235959}}Z &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](https://docs.aws.amazon.com/transcribe/latest/APIReference/API_Reference.html); parameters common to all AWS API operations are listed in the [Common Parameters](https://docs.aws.amazon.com/transcribe/latest/APIReference/CommonParameters.html) section.