speech/snippets/transcribe.py

# Copyright 2017 Google LLC
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""Google Cloud Speech API sample application using the REST API for batch
processing."""

# [START speech_transcribe_sync]
from google.cloud import speech


def transcribe_file(audio_file: str) -> speech.RecognizeResponse:
    """Transcribe the given audio file.
    Args:
        audio_file (str): Path to the local audio file to be transcribed.
            Example: "resources/audio.wav"
    Returns:
        cloud_speech.RecognizeResponse: The response containing the transcription results
    """
    client = speech.SpeechClient()

    # [START speech_python_migration_sync_request]
    # [START speech_python_migration_config]
    with open(audio_file, "rb") as f:
        audio_content = f.read()

    audio = speech.RecognitionAudio(content=audio_content)
    config = speech.RecognitionConfig(
        encoding=speech.RecognitionConfig.AudioEncoding.LINEAR16,
        sample_rate_hertz=16000,
        language_code="en-US",
    )
    # [END speech_python_migration_config]

    # [START speech_python_migration_sync_response]
    response = client.recognize(config=config, audio=audio)

    # [END speech_python_migration_sync_request]
    # Each result is for a consecutive portion of the audio. Iterate through
    # them to get the transcripts for the entire audio file.
    for result in response.results:
        # The first alternative is the most likely one for this portion.
        print(f"Transcript: {result.alternatives[0].transcript}")
    # [END speech_python_migration_sync_response]

    return response


# [END speech_transcribe_sync]


# [START speech_transcribe_sync_gcs]
def transcribe_gcs(audio_uri: str) -> speech.RecognizeResponse:
    """Transcribes the audio file specified by the gcs_uri.
    Args:
        audio_uri (str): The Google Cloud Storage URI of the input audio file.
            E.g., gs://cloud-samples-data/speech/audio.flac
    Returns:
        cloud_speech.RecognizeResponse: The response containing the transcription results
    """
    from google.cloud import speech

    client = speech.SpeechClient()

    # [START speech_python_migration_config_gcs]
    audio = speech.RecognitionAudio(uri=audio_uri)
    config = speech.RecognitionConfig(
        encoding=speech.RecognitionConfig.AudioEncoding.FLAC,
        sample_rate_hertz=16000,
        language_code="en-US",
    )
    # [END speech_python_migration_config_gcs]

    response = client.recognize(config=config, audio=audio)

    # Each result is for a consecutive portion of the audio. Iterate through
    # them to get the transcripts for the entire audio file.
    for result in response.results:
        # The first alternative is the most likely one for this portion.
        print(f"Transcript: {result.alternatives[0].transcript}")

    return response


# [END speech_transcribe_sync_gcs]


if __name__ == "__main__":
    # It could be a local path like: path_to_file = "resources/audio.raw"
    path_to_file = "gs://cloud-samples-data/speech/audio.flac"
    if path_to_file.startswith("gs://"):
        transcribe_gcs(path_to_file)
    else:
        transcribe_file(path_to_file)