Transcribing multi-channel audio files Transcribing multi-channel audio streams

Transcribing multi-channel audio

If you have an audio file or stream that has multiple channels, you can use channel identification to transcribe the speech from each of those channels. Amazon Transcribe Medical transcribes the speech from each channel separately. It combines the separate transcriptions of each channel into a single transcription output.

Use channel identification to identify the separate channels in your audio and transcribe the speech from each of those channels. Enable this in situations such as a caller and agent scenario. Use this to distinguish a caller from an agent in recordings or streams from contact centers that perform drug safety monitoring.

You can enable channel identification for both batch processing and real-time streaming. The following list describes how to enable it for each method.

Batch transcription – AWS Management Console and StartMedicalTranscriptionJob API
Streaming transcription – WebSocket streaming and StartMedicalStreamTranscription API

Transcribing multi-channel audio files

When you transcribe an audio file, Amazon Transcribe Medical returns a list of items for each channel. An item is a transcribed word or punctuation mark. Each word has a start time and an end time. If a person on one channel speaks over a person on a separate channel, the start times and end times of the items for each channel overlap while the individuals are speaking over each other.

By default, you can transcribe audio files with two channels. You can request a quota increase if you need to transcribe files that have more than two channels. For information about requesting a quota increase, see AWS service quotas.

To transcribe multi-channel audio in a batch transcription job, use the AWS Management Console or the StartMedicalTranscriptionJob API.

To use the AWS Management Console to enable channel identification in your batch transcription job, you enable audio identification and then channel identification. Channel identification is a subset of audio identification in the AWS Management Console.

Sign in to the AWS Management Console.
In the navigation pane, under Amazon Transcribe Medical, choose Transcription jobs.
Choose Create job.
On the Specify job details page, provide information about your transcription job.
Choose Next.
Enable Audio identification.
For Audio identification type, choose Channel identification.
Choose Create.

To transcribe a multi-channel audio file (API)

For the StartMedicalTranscriptionJob API, specify the following.
1. For TranscriptionJobName, specify a name unique to your AWS account.
2. For LanguageCode, specify the language code that corresponds to the language spoken in the audio file. The valid value is en-US.
3. For the MediaFileUri parameter of the Media object, specify the name of the media file that you want to transcribe.
4. For the Settings object, set ChannelIdentification to true.

The following is an example request using the AWS SDK for Python (Boto3).



from __future__ import print_function
import time
import boto3
transcribe = boto3.client('transcribe', 'us-west-2')
job_name = "my-first-transcription-job"
job_name = "my-first-med-transcription-job"
job_uri = "s3://DOC-EXAMPLE-BUCKET/my-input-files/my-media-file.flac"
transcribe.start_medical_transcription_job(
      MedicalTranscriptionJobName = job_name,
      Media = {
        'MediaFileUri': job_uri
      },
      OutputBucketName = 'DOC-EXAMPLE-BUCKET',
      OutputKey = 'output-files/',
      LanguageCode = 'en-US',
      Specialty = 'PRIMARYCARE',
      Type = 'CONVERSATION',
      Settings = {
        'ChannelIdentification': True
      }
)
while True:
    status = transcribe.get_transcription_job(MedicalTranscriptionJobName = job_name)
    if status['MedicalTranscriptionJob']['TranscriptionJobStatus'] in ['COMPLETED', 'FAILED']:
        break
    print("Not ready yet...")
    time.sleep(5)
print(status)

To transcribe a multi-channel audio file using a batch transcription job (AWS CLI)

Run the following code.



                    
aws transcribe start-medical-transcription-job \
--region us-west-2 \
--cli-input-json file://example-start-command.json

The following is the code of example-start-command.json.


{
      "MedicalTranscriptionJobName": "my-first-med-transcription-job",        
      "Media": {
          "MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/my-input-files/my-audio-file.flac"
      },
      "OutputBucketName": "DOC-EXAMPLE-BUCKET",
      "OutputKey": "my-output-files/", 
      "LanguageCode": "en-US",
      "Specialty": "PRIMARYCARE",
      "Type": "CONVERSATION",

        "Settings":{
          "ChannelIdentification": true
        }
}

The following code shows the transcription output for an audio file that has a conversation on two channels.



{
  "jobName": "job id",
  "accountId": "111122223333",
  "results": {
    "transcripts": [
      {
        "transcript": "When you try ... It seems to ..."
      }
    ],
    "channel_labels": {
      "channels": [
        {
          "channel_label": "ch_0",
          "items": [
            {
              "start_time": "12.282",
              "end_time": "12.592",
              "alternatives": [
                {
                  "confidence": "1.0000",
                  "content": "When"
                }
              ],
              "type": "pronunciation"
            },
            {
              "start_time": "12.592",
              "end_time": "12.692",
              "alternatives": [
                {
                  "confidence": "0.8787",
                  "content": "you"
                }
              ],
              "type": "pronunciation"
            },
            {
              "start_time": "12.702",
              "end_time": "13.252",
              "alternatives": [
                {
                  "confidence": "0.8318",
                  "content": "try"
                }
              ],
              "type": "pronunciation"
            },
            ...
         ]
      },
      {
          "channel_label": "ch_1",
          "items": [
            {
              "start_time": "12.379",
              "end_time": "12.589",
              "alternatives": [
                {
                  "confidence": "0.5645",
                  "content": "It"
                }
              ],
              "type": "pronunciation"
            },
            {
              "start_time": "12.599",
              "end_time": "12.659",
              "alternatives": [
                {
                  "confidence": "0.2907",
                  "content": "seems"
                }
              ],
              "type": "pronunciation"
            },
            {
              "start_time": "12.669",
              "end_time": "13.029",
              "alternatives": [
                {
                  "confidence": "0.2497",
                  "content": "to"
                }
              ],
              "type": "pronunciation"
            },
            ...
        ]
    }
}

Transcribing multi-channel audio streams

You can transcribe audio from separate channels in either HTTP/2 or WebSocket streams using the StartMedicalStreamTranscription API.

By default, you can transcribe streams with two channels. You can request a quota increase if you need to transcribe streams that have more than two channels. For information about requesting a quota increase, see AWS service quotas.

Transcribing multi-channel audio in an HTTP/2 stream

To transcribe multi-channel audio in an HTTP/2 stream, use the StartMedicalStreamTranscription API and specify the following:

LanguageCode – The language code of the audio. The valid value is en-US.
MediaEncoding – The encoding of the audio. Valid values are ogg-opus, flac, and pcm.
EnableChannelIdentification – true
NumberOfChannels – the number of channels in your streaming audio.

For more information on setting up an HTTP/2 stream to transcribe a medical conversation, see Setting up an HTTP/2 stream.

Transcribing multi-channel audio in a WebSocket stream

To partition speakers in WebSocket streams, use the following format to create a pre-signed URI and start a WebSocket request. Specify enable-channel-identification as true and the number of channels in your stream in number-of-channels. A pre-signed URI contains the information needed to set up bi-directional communication between your application and Amazon Transcribe Medical.



GET wss://transcribestreaming.us-west-2.amazonaws.com:8443/medical-stream-transcription-websocket
?language-code=languageCode
&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=Signature Version 4 signature
&X-Amz-SignedHeaders=host
&media-encoding=flac
&sample-rate=16000
&session-id=sessionId
&enable-channel-identification=true
&number-of-channels=2

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

For more information about WebSocket requests, see Setting up a WebSocket stream.

Multi-channel streaming output

The output of a streaming transcription is the same for HTTP/2 and WebSocket requests. The following is an example output.


{
    "resultId": "XXXXXX-XXXX-XXXX-XXXX-XXXXXXXXXX",
    "startTime": 0.11,
    "endTime": 0.66,
    "isPartial": false,
    "alternatives": [
        {
            "transcript": "Left.",
            "items": [
                {
                    "startTime": 0.11,
                    "endTime": 0.45,
                    "type": "pronunciation",
                    "content": "Left",
                    "vocabularyFilterMatch": false
                },
                {
                    "startTime": 0.45,
                    "endTime": 0.45,
                    "type": "punctuation",
                    "content": ".",
                    "vocabularyFilterMatch": false
                }
            ]
        }
    ],
    "channelId": "ch_0"
}

For each speech segment, there is a channelId flag that indicates which channel the speech belongs to.

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Document Conventions

Partitioning speakers in real-time streams

Transcribing a medical dictation