def transcribe_from_container(uri, properties):
"""
Transcribe all files in the container located at `uri` using the settings specified in `properties`
using the base model for the specified locale.
"""
transcription_definition = cris_client.Transcription(
display_name=NAME,
description=DESCRIPTION,
locale=LOCALE,
content_container_url=uri,
properties=properties)
return transcription_definition
def transcribe_from_single_blob(uri, properties):
"""
Transcribe a single audio file located at `uri` using the settings specified in `properties`
using the base model for the specified locale.
"""
transcription_definition = cris_client.Transcription(
display_name=NAME,
description=DESCRIPTION,
locale=LOCALE,
content_urls=[uri],
properties=properties)
return transcription_definition
def transcribe_with_custom_model(api, uri, properties):
"""
Transcribe a single audio file located at `uri` using the settings specified in `properties`
using the base model for the specified locale.
"""
# Model information (ADAPTED_ACOUSTIC_ID and ADAPTED_LANGUAGE_ID) must be set above.
if MODEL_REFERENCE is None:
logging.error("Custom model ids must be set when using custom models")
sys.exit()
model = api.get_model(MODEL_REFERENCE)
transcription_definition = cris_client.Transcription(
display_name=NAME,
description=DESCRIPTION,
locale=LOCALE,
content_urls=[uri],
model=model,
properties=properties)
return transcription_definition
def retrieve_transcript(identifier, language, speaker_type, service_config):
blob_service_client = BlobServiceClient.from_connection_string(
service_config['connection_string'])
container_client = blob_service_client.get_container_client(identifier)
blob_client = container_client.get_blob_client('audio.wav')
sas_blob = generate_blob_sas(account_name=service_config['account_name'],
container_name=identifier,
blob_name='audio.wav',
account_key=service_config['account_key'],
permission=BlobSasPermissions(read=True),
expiry=datetime.utcnow() +
timedelta(hours=24))
uri = blob_client.url + '?' + sas_blob
logging.info("Starting transcription client...")
# configure API key authorization: subscription_key
configuration = cris_client.Configuration()
configuration.api_key["Ocp-Apim-Subscription-Key"] = service_config[
'subscription_key']
configuration.host = f"https://{service_config['service_region']}.api.cognitive.microsoft.com/speechtotext/v3.0"
# create the client object and authenticate
client = cris_client.ApiClient(configuration)
# create an instance of the transcription api class
api = cris_client.DefaultApi(api_client=client)
try:
# Specify transcription properties by passing a dict to the properties parameter. See
# https://docs.microsoft.com/azure/cognitive-services/speech-service/batch-transcription#configuration-properties
# for supported parameters.
properties = {
"punctuationMode": "Automatic",
"profanityFilterMode": "None",
"wordLevelTimestampsEnabled": True,
"diarizationEnabled": (speaker_type == "both"),
"timeToLive": "PT1H"
}
# Use base models for transcription.
transcription_definition = cris_client.Transcription(
display_name="Simple transcription",
description="Simple transcription description",
locale=language,
content_urls=[uri],
properties=properties)
created_transcription, status, headers = api.create_transcription_with_http_info(
transcription=transcription_definition)
# get the transcription Id from the location URI
transcription_id = headers["location"].split("/")[-1]
# Log information about the created transcription. If you should ask for support, please
# include this information.
logging.info(
f"Created new transcription with id '{transcription_id}' in region {service_config['service_region']}"
)
logging.info("Checking status.")
transcript = {}
completed = False
while not completed:
# wait for 5 seconds before refreshing the transcription status
time.sleep(5)
transcription = api.get_transcription(transcription_id)
logging.info(f"Transcriptions status: {transcription.status}")
if transcription.status in ("Failed", "Succeeded"):
completed = True
if transcription.status == "Succeeded":
pag_files = api.get_transcription_files(transcription_id)
for file_data in _paginate(api, pag_files):
if file_data.kind != "Transcription":
continue
results_url = file_data.links.content_url
results = requests.get(results_url)
transcript = json.loads(results.content)
elif transcription.status == "Failed":
raise Exception(
f"Transcription failed: {transcription.properties.error.message}"
)
finally:
delete_all_transcriptions(api)
return transcript