def transcribe(): logging.info("Starting transcription client...") # configure API key authorization: subscription_key configuration = cris_client.Configuration() configuration.api_key['Ocp-Apim-Subscription-Key'] = SUBSCRIPTION_KEY configuration.host = "https://{}.cris.ai".format(SERVICE_REGION) # create the client object and authenticate client = cris_client.ApiClient(configuration) # create an instance of the transcription api class transcription_api = cris_client.CustomSpeechTranscriptionsApi(api_client=client) # get all transcriptions for the subscription transcriptions: List[cris_client.Transcription] = transcription_api.get_transcriptions() logging.info("Deleting all existing completed transcriptions.") # delete all pre-existing completed transcriptions # if transcriptions are still running or not started, they will not be deleted for transcription in transcriptions: try: transcription_api.delete_transcription(transcription.id) except ValueError: # ignore swagger error on empty response message body: https://github.com/swagger-api/swagger-core/issues/2446 pass # 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': 'DictatedAndAutomatic', # 'ProfanityFilterMode': 'Masked', # 'AddWordLevelTimestamps': 'False', # 'AddDiarization': 'False', # 'AddSentiment': False, # 'TranscriptionResultsContainerUrl': "<results container>" } # Use base models for transcription. Comment this block if you are using a custom model. transcription_definition = cris_client.TranscriptionDefinition( name=NAME, description=DESCRIPTION, locale=LOCALE, recordings_url=RECORDINGS_BLOB_URI, properties=properties ) # Uncomment this block to use custom models for transcription. # Model information (ADAPTED_ACOUSTIC_ID and ADAPTED_LANGUAGE_ID) must be set above. # if ADAPTED_ACOUSTIC_ID is None or ADAPTED_LANGUAGE_ID is None: # logging.info("Custom model ids must be set to when using custom models") # transcription_definition = cris_client.TranscriptionDefinition( # name=NAME, description=DESCRIPTION, locale=LOCALE, recordings_url=RECORDINGS_BLOB_URI, # models=[cris_client.ModelIdentity(ADAPTED_ACOUSTIC_ID), cris_client.ModelIdentity(ADAPTED_LANGUAGE_ID)], # properties=properties # ) data, status, headers = transcription_api.create_transcription_with_http_info(transcription_definition) # extract transcription location from the headers transcription_location: str = headers["location"] # get the transcription Id from the location URI created_transcription: str = transcription_location.split('/')[-1] logging.info("Created new transcription with id {}".format(created_transcription)) logging.info("Checking status.") completed = False while not completed: running, not_started = 0, 0 # get all transcriptions for the user transcriptions: List[cris_client.Transcription] = transcription_api.get_transcriptions() # for each transcription in the list we check the status for transcription in transcriptions: if transcription.status in ("Failed", "Succeeded"): # we check to see if it was the transcription we created from this client if created_transcription != transcription.id: continue completed = True if transcription.status == "Succeeded": results_uri = transcription.results_urls["channel_0"] results = requests.get(results_uri) logging.info("Transcription succeeded. Results: ") logging.info(results.content.decode("utf-8")) else: logging.info("Transcription failed :{}.".format(transcription.status_message)) break elif transcription.status == "Running": running += 1 elif transcription.status == "NotStarted": not_started += 1 logging.info("Transcriptions status: " "completed (this transcription): {}, {} running, {} not started yet".format( completed, running, not_started)) # wait for 5 seconds time.sleep(5) input("Press any key...")
def transcribe(): logging.info("Starting transcription client...") # configure API key authorization: subscription_key configuration = cris_client.Configuration() configuration.api_key['Ocp-Apim-Subscription-Key'] = SUBSCRIPTION_KEY configuration.host = "https://{}.cris.ai".format(SERVICE_REGION) # create the client object and authenticate client = cris_client.ApiClient(configuration) # create an instance of the transcription api class transcription_api = cris_client.CustomSpeechTranscriptionsApi( api_client=client) # Use base models for transcription. Comment this block if you are using a custom model. # Note: you can specify additional transcription properties by passing a # dictionary in the properties parameter. See # https://docs.microsoft.com/azure/cognitive-services/speech-service/batch-transcription # for supported parameters. transcription_definition = cris_client.TranscriptionDefinition( name=NAME, description=DESCRIPTION, locale=LOCALE, recordings_url=RECORDINGS_BLOB_URI) # Uncomment this block to use custom models for transcription. # Model information (ADAPTED_ACOUSTIC_ID and ADAPTED_LANGUAGE_ID) must be set above. # if ADAPTED_ACOUSTIC_ID is None or ADAPTED_LANGUAGE_ID is None: # logging.info("Custom model ids must be set to when using custom models") # transcription_definition = cris_client.TranscriptionDefinition( # name=NAME, description=DESCRIPTION, locale=LOCALE, recordings_url=RECORDINGS_BLOB_URI, # models=[cris_client.ModelIdentity(ADAPTED_ACOUSTIC_ID), cris_client.ModelIdentity(ADAPTED_LANGUAGE_ID)] # ) data, status, headers = transcription_api.create_transcription_with_http_info( transcription_definition) # extract transcription location from the headers transcription_location: str = headers["location"] # get the transcription Id from the location URI created_transcription: str = transcription_location.split('/')[-1] logging.info( "Created new transcription with id {}".format(created_transcription)) logging.info("Checking status.") completed = False while not completed: running, not_started = 0, 0 # get all transcriptions for the user transcriptions: List[ cris_client.Transcription] = transcription_api.get_transcriptions( ) # for each transcription in the list we check the status for transcription in transcriptions: if transcription.status in ("Failed", "Succeeded"): # we check to see if it was the transcription we created from this client if created_transcription != transcription.id: continue completed = True if transcription.status == "Succeeded": results_uri = transcription.results_urls["channel_0"] results = requests.get(results_uri) logging.info("Transcription succeeded. Results: ") logging.info(results.content.decode("utf-8")) else: logging.info("Transcription failed :{}.".format( transcription.status_message)) break elif transcription.status == "Running": running += 1 elif transcription.status == "NotStarted": not_started += 1 logging.info( "Transcriptions status: " "completed (this transcription): {}, {} running, {} not started yet" .format(completed, running, not_started)) # wait for 5 seconds time.sleep(5) input("Press any key...")
def transcribe(self, blob_uri, name='', description='', locale='en-US', properties={}, output_file=None): logging.info("Starting transcription client...") # configure API key authorization: subscription_key configuration = cris_client.Configuration() configuration.api_key['Ocp-Apim-Subscription-Key'] = self.speech_key configuration.host = "https://{}.cris.ai".format(self.service_region) # create the client object and authenticate client = cris_client.ApiClient(configuration) # create an instance of the transcription api class transcription_api = cris_client.CustomSpeechTranscriptionsApi( api_client=client) # get all transcriptions for the subscription transcriptions: List[ cris_client.Transcription] = transcription_api.get_transcriptions( ) logging.info("Deleting all existing completed transcriptions.") # delete all pre-existing completed transcriptions # if transcriptions are still running or not started, they will not be deleted for transcription in transcriptions: try: transcription_api.delete_transcription(transcription.id) except Exception as e: print(e) # 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': 'DictatedAndAutomatic', # 'ProfanityFilterMode': 'Masked', # 'AddWordLevelTimestamps': 'False', # 'AddDiarization': 'False', # 'AddSentiment': False, # 'TranscriptionResultsContainerUrl': "<results container>" # } # Use base models for transcription. Comment this block if you are using a custom model. transcription_definition = cris_client.TranscriptionDefinition( name=name, description=description, locale=locale, recordings_url=blob_uri, properties=properties) data, status, headers = transcription_api.create_transcription_with_http_info( transcription_definition) # extract transcription location from the headers transcription_location: str = headers["location"] # get the transcription Id from the location URI created_transcription: str = transcription_location.split('/')[-1] logging.info("Created new transcription with id {}".format( created_transcription)) logging.info("Checking status.") completed = False while not completed: running, not_started = 0, 0 # get all transcriptions for the user transcriptions: List[ cris_client. Transcription] = transcription_api.get_transcriptions() # for each transcription in the list we check the status for transcription in transcriptions: if transcription.status in ("Failed", "Succeeded"): # we check to see if it was the transcription we created from this client if created_transcription != transcription.id: continue completed = True if transcription.status == "Succeeded": results_uri = transcription.results_urls["channel_0"] results = requests.get(results_uri) logging.info("Transcription succeeded. Results: ") logging.info( "######### TRANSCRIPTION BEGIN ########## ") logging.info(results.content.decode("utf-8")) if (output_file): json_file = open(output_file, 'w') json_file.write( json.loads( json.dumps(results.content.decode("utf-8"), ensure_ascii=False))) logging.info("######### TRANSCRIPTION END ########## ") else: logging.info("Transcription failed :{}.".format( transcription.status_message)) break elif transcription.status == "Running": running += 1 elif transcription.status == "NotStarted": not_started += 1 logging.info( "Transcriptions status: " "completed (this transcription): {}, {} running, {} not started yet" .format(completed, running, not_started)) # wait for 5 seconds time.sleep(5)
def transcribe(url): logging.info("Starting transcription client...") # Your subscription key and region for the speech service SUBSCRIPTION_KEY = "" SERVICE_REGION = "southcentralus" NAME = "Simple transcription" DESCRIPTION = "Simple transcription description" LOCALE = "en-US" # Set subscription information when doing transcription with custom models ADAPTED_ACOUSTIC_ID = None # guid of a custom acoustic model ADAPTED_LANGUAGE_ID = None # guid of a custom language model # configure API key authorization: subscription_key configuration = cris_client.Configuration() configuration.api_key['Ocp-Apim-Subscription-Key'] = SUBSCRIPTION_KEY configuration.host = "https://{}.cris.ai".format(SERVICE_REGION) # create the client object and authenticate client = cris_client.ApiClient(configuration) # create an instance of the transcription api class transcription_api = cris_client.CustomSpeechTranscriptionsApi(api_client=client) # get all transcriptions for the subscription transcriptions: List[cris_client.Transcription] = transcription_api.get_transcriptions() logging.info("Deleting all existing completed transcriptions.") # delete all pre-existing completed transcriptions # if transcriptions are still running or not started, they will not be deleted for transcription in transcriptions: try: transcription_api.delete_transcription(transcription.id) except ValueError: # ignore swagger error on empty response message body: https://github.com/swagger-api/swagger-core/issues/2446 pass # Use base models for transcription. Comment this block if you are using a custom model. # Note: you can specify additional transcription properties by passing a # dictionary in the properties parameter. See # https://docs.microsoft.com/azure/cognitive-services/speech-service/batch-transcription # for supported parameters. logging.info("Printing URL ::: {}".format(url)) transcription_definition = cris_client.TranscriptionDefinition( name=NAME, description=DESCRIPTION, locale=LOCALE, recordings_url=url ) # Uncomment this block to use custom models for transcription. # Model information (ADAPTED_ACOUSTIC_ID and ADAPTED_LANGUAGE_ID) must be set above. # if ADAPTED_ACOUSTIC_ID is None or ADAPTED_LANGUAGE_ID is None: # logging.info("Custom model ids must be set to when using custom models") # transcription_definition = cris_client.TranscriptionDefinition( # name=NAME, description=DESCRIPTION, locale=LOCALE, recordings_url=RECORDINGS_BLOB_URI, # models=[cris_client.ModelIdentity(ADAPTED_ACOUSTIC_ID), cris_client.ModelIdentity(ADAPTED_LANGUAGE_ID)] # ) data, status, headers = transcription_api.create_transcription_with_http_info(transcription_definition) # extract transcription location from the headers transcription_location: str = headers["location"] # get the transcription Id from the location URI created_transcription: str = transcription_location.split('/')[-1] logging.info("Created new transcription with id {}".format(created_transcription)) logging.info("Checking status.") completed = False while not completed: running, not_started = 0, 0 # get all transcriptions for the user transcriptions: List[cris_client.Transcription] = transcription_api.get_transcriptions() # for each transcription in the list we check the status for transcription in transcriptions: if transcription.status in ("Failed", "Succeeded"): # we check to see if it was the transcription we created from this client if created_transcription != transcription.id: continue completed = True if transcription.status == "Succeeded": results_uri = transcription.results_urls["channel_0"] results = requests.get(results_uri) logging.info("Transcription succeeded. Results: ") logging.info(results.content.decode("utf-8")) return results.content.decode("utf-8") else: logging.info("Transcription failed :{}.".format(transcription.status_message)) break elif transcription.status == "Running": running += 1 elif transcription.status == "NotStarted": not_started += 1 logging.info("Transcriptions status: " "completed (this transcription): {}, {} running, {} not started yet".format( completed, running, not_started)) # wait for 5 seconds time.sleep(5)
def transcribe(): logging.info("Starting transcription client...") # configure API key authorization: subscription_key configuration = cris_client.Configuration() configuration.api_key['Ocp-Apim-Subscription-Key'] = SUBSCRIPTION_KEY # create the client object and authenticate client = cris_client.ApiClient(configuration) # create an instance of the transcription api class transcription_api = cris_client.CustomSpeechTranscriptionsApi( api_client=client) # get all transcriptions for the subscription transcriptions: List[ cris_client.Transcription] = transcription_api.get_transcriptions() logging.info("Deleting all existing completed transcriptions.") # delete all pre-existing completed transcriptions # if transcriptions are still running or not started, they will not be deleted for transcription in transcriptions: try: transcription_api.delete_transcription(transcription.id) except ValueError: # ignore swagger error on empty response message body: https://github.com/swagger-api/swagger-core/issues/2446 pass logging.info("Creating transcriptions.") # https://docs.microsoft.com/azure/cognitive-services/speech-service/batch-transcription properties = {'AddWordLevelTimestamps': 'True', 'AddDiarization': 'True'} transcription_definition = cris_client.TranscriptionDefinition( name=NAME, description=DESCRIPTION, locale=LOCALE, recordings_url=RECORDINGS_BLOB_URI, properties=properties) data, status, headers = transcription_api.create_transcription_with_http_info( transcription_definition) # extract transcription location from the headers transcription_location: str = headers["location"] # get the transcription Id from the location URI created_transcription: str = transcription_location.split('/')[-1] logging.info("Checking status.") completed = False while not completed: running, not_started = 0, 0 # get all transcriptions for the user transcriptions: List[ cris_client.Transcription] = transcription_api.get_transcriptions( ) # for each transcription in the list we check the status for transcription in transcriptions: if transcription.status in ("Failed", "Succeeded"): # we check to see if it was one of the transcriptions we created from this client if created_transcription != transcription.id: continue completed = True if transcription.status == "Succeeded": results_uri = transcription.results_urls["channel_0"] results = requests.get(results_uri) logging.info("Transcription succeeded. Results: ") logging.info(results.content.decode("utf-8")) else: logging.info("Transcription failed :{}.".format( transcription.status_message)) elif transcription.status == "Running": running += 1 elif transcription.status == "NotStarted": not_started += 1 logging.info( "Transcriptions status: " "completed (this transcription): {}, {} running, {} not started yet" .format(completed, running, not_started)) time.sleep(5) sys.exit()
def transcribe(): logging.info("Starting transcription client...") # configure API key authorization: subscription_key configuration = cris_client.Configuration() configuration.api_key['Ocp-Apim-Subscription-Key'] = SUBSCRIPTION_KEY # create the client object and authenticate client = cris_client.ApiClient(configuration) # create an instance of the transcription api class transcription_api = cris_client.CustomSpeechTranscriptionsApi( api_client=client) # get all transcriptions for the subscription transcriptions: List[ cris_client.Transcription] = transcription_api.get_transcriptions() logging.info("Deleting all existing completed transcriptions.") # delete all pre-existing completed transcriptions # if transcriptions are still running or not started, they will not be deleted for transcription in transcriptions: transcription_api.delete_transcription(transcription.id) logging.info("Creating transcriptions.") # Use base models for transcription. Comment this block if you are using a custom model. transcription_definition = cris_client.TranscriptionDefinition( name=NAME, description=DESCRIPTION, locale=LOCALE, recordings_url=RECORDINGS_BLOB_URI) # Uncomment this block to use custom models for transcription. # Model information (ADAPTED_ACOUSTIC_ID and ADAPTED_LANGUAGE_ID) must be set above. # if ADAPTED_ACOUSTIC_ID is None or ADAPTED_LANGUAGE_ID is None: # logging.info("Custom model ids must be set to when using custom models") # transcription_definition = cris_client.TranscriptionDefinition( # name=NAME, description=DESCRIPTION, locale=LOCALE, recordings_url=RECORDINGS_BLOB_URI, # models=[cris_client.ModelIdentity(ADAPTED_ACOUSTIC_ID), cris_client.ModelIdentity(ADAPTED_LANGUAGE_ID)] # ) data, status, headers = transcription_api.create_transcription_with_http_info( transcription_definition) # extract transcription location from the headers transcription_location: str = headers["location"] # get the transcription Id from the location URI created_transcription: str = transcription_location.split('/')[-1] logging.info("Checking status.") completed = False running, not_started = 0, 0 while not completed: # get all transcriptions for the user transcriptions: List[ cris_client.Transcription] = transcription_api.get_transcriptions( ) # for each transcription in the list we check the status for transcription in transcriptions: if transcription.status == "Failed" or transcription.status == "Succeeded": # we check to see if it was one of the transcriptions we created from this client if created_transcription != transcription.id: continue completed = True if transcription.status == "Succeeded": results_uri = transcription.results_urls["channel_0"] results = requests.get(results_uri) logging.info("Transcription succeeded. Results: ") logging.info(results.content.decode("utf-8")) elif transcription.status == "Running": running += 1 elif transcription.status == "NotStarted": not_started += 1 logging.info( "Transcriptions status: " "completed (this transcription): {}, {} running, {} not started yet" .format(completed, running, not_started)) # wait for 5 seconds time.sleep(5) input("Press any key...")
def transcribe(): logging.info("Starting transcription client...") # configure API key authorization: subscription_key configuration = cris_client.Configuration() configuration.api_key["Ocp-Apim-Subscription-Key"] = SUBSCRIPTION_KEY configuration.host = f"https://{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.CustomSpeechTranscriptionsApi(api_client=client) # 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": "DictatedAndAutomatic", # "profanityFilterMode": "Masked", # "wordLevelTimestampsEnabled": True, # "diarizationEnabled": True, # "destinationContainerUrl": "<SAS Uri with at least write (w) permissions for an Azure Storage blob container that results should be written to>", # "timeToLive": "PT1H" } # Use base models for transcription. Comment this block if you are using a custom model. transcription_definition = transcribe_from_single_blob( RECORDINGS_BLOB_URI, properties) # Uncomment this block to use custom models for transcription. # transcription_definition = transcribe_with_custom_model(api, RECORDINGS_BLOB_URI, properties) # Uncomment this block to transcribe all files from a container. # transcription_definition = transcribe_from_container(RECORDINGS_CONTAINER_URI, 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_REGION}" ) logging.info("Checking status.") 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 audiofilename = file_data.name results_url = file_data.links.content_url results = requests.get(results_url) logging.info( f"Results for {audiofilename}:\n{results.content.decode('utf-8')}" ) elif transcription.status == "Failed": logging.info( f"Transcription failed: {transcription.properties.error.message}" )
def transcribe(): logging.info("Starting transcription client...") # APIキー認証の構成 configuration = cris_client.Configuration() configuration.api_key["Ocp-Apim-Subscription-Key"] = SUBSCRIPTION_KEY configuration.host = "https://{}.cris.ai".format(SERVICE_REGION) # clientオブジェクトの生成 client = cris_client.ApiClient(configuration) # transcription apiクラスのインスタンス生成 transcription_api = cris_client.CustomSpeechTranscriptionsApi( api_client=client) # ベースモデルを使ったtranscriptionの定義 transcription_definition = cris_client.TranscriptionDefinition( name=NAME, description=DESCRIPTION, locale=LOCALE, recordings_url=RECORDINGS_BLOB_URI) data, status, headers = transcription_api.create_transcription_with_http_info( transcription_definition) # locationの取得 transcription_location: str = headers["location"] # transcription idの取得 created_transcription: str = transcription_location.split("/")[-1] logging.info( "Created new transcription with id {}".format(created_transcription)) logging.info("Checking status...") completed = False while not completed: running, not_started = 0, 0 # transcriptionの実行 transcriptions: List[ cris_client.Transcription] = transcription_api.get_transcriptions( ) for transcription in transcriptions: if transcription.status in ("Failed", "Succeeded"): if created_transcription != transcription.id: continue completed = True if transcription.status == "Succeeded": results_uri = transcription.results_urls["channel_0"] results = requests.get(results_uri) logging.info("Transcription succeeded. Results: ") logging.info(results.content.decode("utf-8")) else: logging.info("Transaction failed :{}.".format( transcription.status_message)) break elif transcription.status == "Running": running += 1 elif transcription.status == "NotStarted": not_started += 1 logging.info( "Transctions status: " "completed (this transcription): {}, {} running, {} not started yet" .format(completed, running, not_started)) time.sleep(5) input("Press any key...")
def transcribe(outfile, file_name): block_blob_service = BlockBlobService(account_name=ACCOUNT_NAME, account_key=ACCOUNT_KEY) container_name = "youcook2-videos-audio" blob_name = 'train/' + file_name + '.wav' sas_url = block_blob_service.generate_blob_shared_access_signature( container_name, blob_name, permission=BlobPermissions.READ, expiry=datetime.utcnow() + timedelta(hours=1), start=datetime.utcnow()) print(sas_url) recordings_blob_uri = URI_PREFIX + '/' + blob_name + '?' + sas_url print(recordings_blob_uri) logging.info("Starting transcription client...") # configure API key authorization: subscription_key configuration = cris_client.Configuration() configuration.api_key['Ocp-Apim-Subscription-Key'] = SUBSCRIPTION_KEY # create the client object and authenticate client = cris_client.ApiClient(configuration) # create an instance of the transcription api class transcription_api = cris_client.CustomSpeechTranscriptionsApi( api_client=client) # get all transcriptions for the subscription transcriptions: List[ cris_client.Transcription] = transcription_api.get_transcriptions() #logging.info("Deleting all existing completed transcriptions.") # delete all pre-existing completed transcriptions # if transcriptions are still running or not started, they will not be deleted #for transcription in transcriptions: # try: # transcription_api.delete_transcription(transcription.id) # except ValueError: # ignore swagger error on empty response message body: https://github.com/swagger-api/swagger-core/issues/2446 # pass logging.info("Creating transcriptions.") # Use base models for transcription. Comment this block if you are using a custom model. # Note: you can specify additional transcription properties by passing a # dictionary in the properties parameter. See # https://docs.microsoft.com/azure/cognitive-services/speech-service/batch-transcription # for supported parameters. transcription_definition = cris_client.TranscriptionDefinition( name=NAME, description=DESCRIPTION, locale=LOCALE, recordings_url=recordings_blob_uri) # Uncomment this block to use custom models for transcription. # Model information (ADAPTED_ACOUSTIC_ID and ADAPTED_LANGUAGE_ID) must be set above. # if ADAPTED_ACOUSTIC_ID is None or ADAPTED_LANGUAGE_ID is None: # logging.info("Custom model ids must be set to when using custom models") # transcription_definition = cris_client.TranscriptionDefinition( # name=NAME, description=DESCRIPTION, locale=LOCALE, recordings_url=RECORDINGS_BLOB_URI, # models=[cris_client.ModelIdentity(ADAPTED_ACOUSTIC_ID), cris_client.ModelIdentity(ADAPTED_LANGUAGE_ID)] # ) data, status, headers = transcription_api.create_transcription_with_http_info( transcription_definition) # extract transcription location from the headers transcription_location: str = headers["location"] # get the transcription Id from the location URI created_transcription: str = transcription_location.split('/')[-1] logging.info("Checking status.") completed = False while not completed: running, not_started = 0, 0 # get all transcriptions for the user transcriptions: List[ cris_client.Transcription] = transcription_api.get_transcriptions( ) # for each transcription in the list we check the status for transcription in transcriptions: if transcription.status in ("Failed", "Succeeded"): # we check to see if it was one of the transcriptions we created from this client if created_transcription != transcription.id: continue completed = True if transcription.status == "Succeeded": results_uri = transcription.results_urls["channel_0"] results = requests.get(results_uri) logging.info("Transcription succeeded. Results: ") with open(outfile, 'w', encoding='utf-8') as f: json.dump(results.json(), f, ensure_ascii=False, indent=4) else: logging.info("Transcription failed :{}.".format( transcription.status_message)) elif transcription.status == "Running": running += 1 elif transcription.status == "NotStarted": not_started += 1 logging.info( "Transcriptions status: " "completed (this transcription): {}, {} running, {} not started yet" .format(completed, running, not_started)) # wait for 10 seconds time.sleep(10)