File: //lib/python3/dist-packages/awscli/examples/transcribe/start-transcription-job.rst
**Example 1: To transcribe an audio file**
The following ``start-transcription-job`` example transcribes your audio file. ::
aws transcribe start-transcription-job \
--cli-input-json file://myfile.json
Contents of ``myfile.json``::
{
"TranscriptionJobName": "cli-simple-transcription-job",
"LanguageCode": "the-language-of-your-transcription-job",
"Media": {
"MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
}
}
For more information, see `Getting Started (AWS Command Line Interface) <https://docs.aws.amazon.com/transcribe/latest/dg/getting-started-cli.html>`__ in the *Amazon Transcribe Developer Guide*.
**Example 2: To transcribe a multi-channel audio file**
The following ``start-transcription-job`` example transcribes your multi-channel audio file. ::
aws transcribe start-transcription-job \
--cli-input-json file://mysecondfile.json
Contents of ``mysecondfile.json``::
{
"TranscriptionJobName": "cli-channelid-job",
"LanguageCode": "the-language-of-your-transcription-job",
"Media": {
"MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
},
"Settings":{
"ChannelIdentification":true
}
}
Output::
{
"TranscriptionJob": {
"TranscriptionJobName": "cli-channelid-job",
"TranscriptionJobStatus": "IN_PROGRESS",
"LanguageCode": "the-language-of-your-transcription-job",
"Media": {
"MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
},
"StartTime": "2020-09-17T16:07:56.817000+00:00",
"CreationTime": "2020-09-17T16:07:56.784000+00:00",
"Settings": {
"ChannelIdentification": true
}
}
}
For more information, see `Transcribing Multi-Channel Audio <https://docs.aws.amazon.com/transcribe/latest/dg/channel-id.html>`__ in the *Amazon Transcribe Developer Guide*.
**Example 3: To transcribe an audio file and identify the different speakers**
The following ``start-transcription-job`` example transcribes your audio file and identifies the speakers in the transcription output. ::
aws transcribe start-transcription-job \
--cli-input-json file://mythirdfile.json
Contents of ``mythirdfile.json``::
{
"TranscriptionJobName": "cli-speakerid-job",
"LanguageCode": "the-language-of-your-transcription-job",
"Media": {
"MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
},
"Settings":{
"ShowSpeakerLabels": true,
"MaxSpeakerLabels": 2
}
}
Output::
{
"TranscriptionJob": {
"TranscriptionJobName": "cli-speakerid-job",
"TranscriptionJobStatus": "IN_PROGRESS",
"LanguageCode": "the-language-of-your-transcription-job",
"Media": {
"MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
},
"StartTime": "2020-09-17T16:22:59.696000+00:00",
"CreationTime": "2020-09-17T16:22:59.676000+00:00",
"Settings": {
"ShowSpeakerLabels": true,
"MaxSpeakerLabels": 2
}
}
}
For more information, see `Identifying Speakers <https://docs.aws.amazon.com/transcribe/latest/dg/diarization.html>`__ in the *Amazon Transcribe Developer Guide*.
**Example 4: To transcribe an audio file and mask any unwanted words in the transcription output**
The following ``start-transcription-job`` example transcribes your audio file and uses a vocabulary filter you've previously created to mask any unwanted words. ::
aws transcribe start-transcription-job \
--cli-input-json file://myfourthfile.json
Contents of ``myfourthfile.json``::
{
"TranscriptionJobName": "cli-filter-mask-job",
"LanguageCode": "the-language-of-your-transcription-job",
"Media": {
"MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
},
"Settings":{
"VocabularyFilterName": "your-vocabulary-filter",
"VocabularyFilterMethod": "mask"
}
}
Output::
{
"TranscriptionJob": {
"TranscriptionJobName": "cli-filter-mask-job",
"TranscriptionJobStatus": "IN_PROGRESS",
"LanguageCode": "the-language-of-your-transcription-job",
"Media": {
"MediaFileUri": "s3://Amazon-S3-Prefix/your-media-file.file-extension"
},
"StartTime": "2020-09-18T16:36:18.568000+00:00",
"CreationTime": "2020-09-18T16:36:18.547000+00:00",
"Settings": {
"VocabularyFilterName": "your-vocabulary-filter",
"VocabularyFilterMethod": "mask"
}
}
}
For more information, see `Filtering Transcriptions <https://docs.aws.amazon.com/transcribe/latest/dg/filter-transcriptions.html>`__ in the *Amazon Transcribe Developer Guide*.
**Example 5: To transcribe an audio file and remove any unwanted words in the transcription output**
The following ``start-transcription-job`` example transcribes your audio file and uses a vocabulary filter you've previously created to mask any unwanted words. ::
aws transcribe start-transcription-job \
--cli-input-json file://myfifthfile.json
Contents of ``myfifthfile.json``::
{
"TranscriptionJobName": "cli-filter-remove-job",
"LanguageCode": "the-language-of-your-transcription-job",
"Media": {
"MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
},
"Settings":{
"VocabularyFilterName": "your-vocabulary-filter",
"VocabularyFilterMethod": "remove"
}
}
Output::
{
"TranscriptionJob": {
"TranscriptionJobName": "cli-filter-remove-job",
"TranscriptionJobStatus": "IN_PROGRESS",
"LanguageCode": "the-language-of-your-transcription-job",
"Media": {
"MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
},
"StartTime": "2020-09-18T16:36:18.568000+00:00",
"CreationTime": "2020-09-18T16:36:18.547000+00:00",
"Settings": {
"VocabularyFilterName": "your-vocabulary-filter",
"VocabularyFilterMethod": "remove"
}
}
}
For more information, see `Filtering Transcriptions <https://docs.aws.amazon.com/transcribe/latest/dg/filter-transcriptions.html>`__ in the *Amazon Transcribe Developer Guide*.
**Example 6: To transcribe an audio file with increased accuracy using a custom vocabulary**
The following ``start-transcription-job`` example transcribes your audio file and uses a vocabulary filter you've previously created to mask any unwanted words. ::
aws transcribe start-transcription-job \
--cli-input-json file://mysixthfile.json
Contents of ``mysixthfile.json``::
{
"TranscriptionJobName": "cli-vocab-job",
"LanguageCode": "the-language-of-your-transcription-job",
"Media": {
"MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
},
"Settings":{
"VocabularyName": "your-vocabulary"
}
}
Output::
{
"TranscriptionJob": {
"TranscriptionJobName": "cli-vocab-job",
"TranscriptionJobStatus": "IN_PROGRESS",
"LanguageCode": "the-language-of-your-transcription-job",
"Media": {
"MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
},
"StartTime": "2020-09-18T16:36:18.568000+00:00",
"CreationTime": "2020-09-18T16:36:18.547000+00:00",
"Settings": {
"VocabularyName": "your-vocabulary"
}
}
}
For more information, see `Filtering Transcriptions <https://docs.aws.amazon.com/transcribe/latest/dg/filter-transcriptions.html>`__ in the *Amazon Transcribe Developer Guide*.
**Example 7: To identify the language of an audio file and transcribe it**
The following ``start-transcription-job`` example transcribes your audio file and uses a vocabulary filter you've previously created to mask any unwanted words. ::
aws transcribe start-transcription-job \
--cli-input-json file://myseventhfile.json
Contents of ``myseventhfile.json``::
{
"TranscriptionJobName": "cli-identify-language-transcription-job",
"IdentifyLanguage": true,
"Media": {
"MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
}
}
Output::
{
"TranscriptionJob": {
"TranscriptionJobName": "cli-identify-language-transcription-job",
"TranscriptionJobStatus": "IN_PROGRESS",
"Media": {
"MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/Amazon-S3-prefix/your-media-file-name.file-extension"
},
"StartTime": "2020-09-18T22:27:23.970000+00:00",
"CreationTime": "2020-09-18T22:27:23.948000+00:00",
"IdentifyLanguage": true
}
}
For more information, see `Identifying the Language <https://docs.aws.amazon.com/transcribe/latest/dg/auto-lang-id.html>`__ in the *Amazon Transcribe Developer Guide*.
**Example 8: To transcribe an audio file with personally identifiable information redacted**
The following ``start-transcription-job`` example transcribes your audio file and redacts any personally identifiable information in the transcription output. ::
aws transcribe start-transcription-job \
--cli-input-json file://myeighthfile.json
Contents of ``myeigthfile.json``::
{
"TranscriptionJobName": "cli-redaction-job",
"LanguageCode": "language-code",
"Media": {
"MediaFileUri": "s3://Amazon-S3-Prefix/your-media-file.file-extension"
},
"ContentRedaction": {
"RedactionOutput":"redacted",
"RedactionType":"PII"
}
}
Output::
{
"TranscriptionJob": {
"TranscriptionJobName": "cli-redaction-job",
"TranscriptionJobStatus": "IN_PROGRESS",
"LanguageCode": "language-code",
"Media": {
"MediaFileUri": "s3://Amazon-S3-Prefix/your-media-file.file-extension"
},
"StartTime": "2020-09-25T23:49:13.195000+00:00",
"CreationTime": "2020-09-25T23:49:13.176000+00:00",
"ContentRedaction": {
"RedactionType": "PII",
"RedactionOutput": "redacted"
}
}
}
For more information, see `Automatic Content Redaction <https://docs.aws.amazon.com/transcribe/latest/dg/content-redaction.html>`__ in the *Amazon Transcribe Developer Guide*.
**Example 9: To generate a transcript with personally identifiable information (PII) redacted and an unredacted transcript**
The following ``start-transcription-job`` example generates two transcrptions of your audio file, one with the personally identifiable information redacted, and the other without any redactions. ::
aws transcribe start-transcription-job \
--cli-input-json file://myninthfile.json
Contents of ``myninthfile.json``::
{
"TranscriptionJobName": "cli-redaction-job-with-unredacted-transcript",
"LanguageCode": "language-code",
"Media": {
"MediaFileUri": "s3://Amazon-S3-Prefix/your-media-file.file-extension"
},
"ContentRedaction": {
"RedactionOutput":"redacted_and_unredacted",
"RedactionType":"PII"
}
}
Output::
{
"TranscriptionJob": {
"TranscriptionJobName": "cli-redaction-job-with-unredacted-transcript",
"TranscriptionJobStatus": "IN_PROGRESS",
"LanguageCode": "language-code",
"Media": {
"MediaFileUri": "s3://Amazon-S3-Prefix/your-media-file.file-extension"
},
"StartTime": "2020-09-25T23:59:47.677000+00:00",
"CreationTime": "2020-09-25T23:59:47.653000+00:00",
"ContentRedaction": {
"RedactionType": "PII",
"RedactionOutput": "redacted_and_unredacted"
}
}
}
For more information, see `Automatic Content Redaction <https://docs.aws.amazon.com/transcribe/latest/dg/content-redaction.html>`__ in the *Amazon Transcribe Developer Guide*.
**Example 10: To use a custom language model you've previously created to transcribe an audio file.**
The following ``start-transcription-job`` example transcribes your audio file with a custom language model you've previously created. ::
aws transcribe start-transcription-job \
--cli-input-json file://mytenthfile.json
Contents of ``mytenthfile.json``::
{
"TranscriptionJobName": "cli-clm-2-job-1",
"LanguageCode": "language-code",
"Media": {
"MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/your-audio-file.file-extension"
},
"ModelSettings": {
"LanguageModelName":"cli-clm-2"
}
}
Output::
{
"TranscriptionJob": {
"TranscriptionJobName": "cli-clm-2-job-1",
"TranscriptionJobStatus": "IN_PROGRESS",
"LanguageCode": "language-code",
"Media": {
"MediaFileUri": "s3://DOC-EXAMPLE-BUCKET/your-audio-file.file-extension"
},
"StartTime": "2020-09-28T17:56:01.835000+00:00",
"CreationTime": "2020-09-28T17:56:01.801000+00:00",
"ModelSettings": {
"LanguageModelName": "cli-clm-2"
}
}
}
For more information, see `Improving Domain-Specific Transcription Accuracy with Custom Language Models <https://docs.aws.amazon.com/transcribe/latest/dg/custom-language-models.html>`__ in the *Amazon Transcribe Developer Guide*.