Google Cloud Text to Speech Operators¶

Prerequisite Tasks¶

To use these operators, you must do a few things:

Select or create a Cloud Platform project using Cloud Console.

Enable billing for your project, as described in Google Cloud documentation.

Enable API, as described in Cloud Console documentation.
Install API libraries via pip.
pip install 'apache-airflow[gcp]'
Detailed information is available Installation
Setup Connection.

GcpTextToSpeechSynthesizeOperator¶

Synthesizes text to audio file and stores it to Google Cloud Storage

For parameter definition, take a look at airflow.contrib.operators.gcp_text_to_speech_operator.GcpTextToSpeechSynthesizeOperator

Arguments¶

Some arguments in the example DAG are taken from the OS environment variables:

airflow/contrib/example_dags/example_gcp_speech.pyView Source

GCP_PROJECT_ID = os.environ.get("GCP_PROJECT_ID", "example-project")
BUCKET_NAME = os.environ.get("GCP_SPEECH_TEST_BUCKET", "gcp-speech-test-bucket")

input, voice and audio_config arguments need to be dicts or objects of corresponding classes from google.cloud.texttospeech_v1.types module

for more information, see: https://googleapis.github.io/google-cloud-python/latest/texttospeech/gapic/v1/api.html#google.cloud.texttospeech_v1.TextToSpeechClient.synthesize_speech

airflow/contrib/example_dags/example_gcp_speech.pyView Source

INPUT = {"text": "Sample text for demo purposes"}
VOICE = {"language_code": "en-US", "ssml_gender": "FEMALE"}
AUDIO_CONFIG = {"audio_encoding": "LINEAR16"}

filename is a simple string argument:

airflow/contrib/example_dags/example_gcp_speech.pyView Source

FILENAME = "gcp-speech-test-file"

Using the operator¶

airflow/contrib/example_dags/example_gcp_speech.pyView Source

text_to_speech_synthesize_task = GcpTextToSpeechSynthesizeOperator(
    project_id=GCP_PROJECT_ID,
    input_data=INPUT,
    voice=VOICE,
    audio_config=AUDIO_CONFIG,
    target_bucket_name=BUCKET_NAME,
    target_filename=FILENAME,
    task_id="text_to_speech_synthesize_task",
)

Templating¶

template_fields = (
    "input_data",
    "voice",
    "audio_config",
    "project_id",
    "gcp_conn_id",
    "target_bucket_name",
    "target_filename",
)

Google Cloud Speech to Text Operators¶

GcpSpeechToTextRecognizeSpeechOperator¶

Recognizes speech in audio input and returns text.

For parameter definition, take a look at airflow.contrib.operators.gcp_speech_to_text_operator.GcpSpeechToTextRecognizeSpeechOperator

Arguments¶

config and audio arguments need to be dicts or objects of corresponding classes from google.cloud.speech_v1.types module

for more information, see: https://googleapis.github.io/google-cloud-python/latest/speech/gapic/v1/api.html#google.cloud.speech_v1.SpeechClient.recognize

airflow/contrib/example_dags/example_gcp_speech.pyView Source

INPUT = {"text": "Sample text for demo purposes"}
VOICE = {"language_code": "en-US", "ssml_gender": "FEMALE"}
AUDIO_CONFIG = {"audio_encoding": "LINEAR16"}

filename is a simple string argument:

airflow/contrib/example_dags/example_gcp_speech.pyView Source

CONFIG = {"encoding": "LINEAR16", "language_code": "en_US"}
AUDIO = {"uri": "gs://{bucket}/{object}".format(bucket=BUCKET_NAME, object=FILENAME)}

Using the operator¶

airflow/contrib/example_dags/example_gcp_speech.pyView Source

speech_to_text_recognize_task = GcpSpeechToTextRecognizeSpeechOperator(
    project_id=GCP_PROJECT_ID, config=CONFIG, audio=AUDIO, task_id="speech_to_text_recognize_task"
)

Templating¶

template_fields = ("audio", "config", "project_id", "gcp_conn_id", "timeout")

Reference¶

For further information, look at: