The ML.TRANSCRIBE function

This document describes the ML.TRANSCRIBE function, which lets you transcribe audio files from an object table by using the Speech-to-Text API.

Syntax

ML.TRANSCRIBE(
  MODEL `project_id.dataset.model_name`,
  TABLE `project_id.dataset.object_table`,
  [RECOGNITION_CONFIG => ( JSON 'recognition_config')]
)

Arguments

ML.TRANSCRIBE takes the following arguments:

Output

ML.TRANSCRIBE returns the following columns:

Quotas

See Cloud AI service functions quotas and limits.

Known issues

Sometimes after a query job that uses this function finishes successfully, some returned rows contain the following error message:

A retryable error occurred: RESOURCE EXHAUSTED error from <remote endpoint>

This issue occurs because BigQuery query jobs finish successfully even if the function fails for some of the rows. The function fails when the volume of API calls to the remote endpoint exceeds the quota limits for that service. This issue occurs most often when you are running multiple parallel batch queries. BigQuery retries these calls, but if the retries fail, the resource exhausted error message is returned.

Locations

ML.TRANSCRIBE must run in the same region as the remote model that the function references. For more information about supported locations for models based on the Speech-to-Text, see Locations for remote models.

Limitations

The function can't process audio files that are longer than 1 minute. Any row that contains such a file returns an error.

Example

The following example transcribes the audio files represented by the audio table:

Create the model:

# Create model
CREATE OR REPLACE MODEL
`myproject.mydataset.transcribe_model`
REMOTE WITH CONNECTION `myproject.myregion.myconnection`
OPTIONS (remote_service_type = 'CLOUD_AI_SPEECH_TO_TEXT_V2',
speech_recognizer = 'projects/project_number/locations/recognizer_location/recognizer/recognizer_id');

Transcribe the audio files without overriding the recognizer's default configuration:

SELECT *
FROM ML.TRANSCRIBE(
  MODEL `myproject.mydataset.transcribe_model`,
  TABLE `myproject.mydataset.audio`
);

Transcribe the audio files and override the recognizer's default configuration:

SELECT *
FROM ML.TRANSCRIBE(
  MODEL `myproject.mydataset.transcribe_model`,
  TABLE `myproject.mydataset.audio`,
  recognition_config => ( JSON '{"language_codes": ["en-US" ],"model": "telephony","auto_decoding_config": {}}')
);

The result is similar to the following:

transcripts ml_transcribe_result ml_transcribe_status uri ...
OK Google stream stranger things from Netflix to my TV. Okay, stranger things from Netflix playing on t v smart home and it's just... {"metadata":{"total_billed_duration":{"seconds":56}},"results":[{"alternatives":[{"confidence":0.738729,"transcript"... gs://mybucket/audio_files

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