Transcribe Word Time Offsets

This sample demonstrates how to transcribe audio with word time offsets using the Speech-to-Text API.

Code sample

Python

To learn how to install and use the client library for Cloud STT, see Cloud STT client libraries. For more information, see the Cloud STT Python API reference documentation.

To authenticate to Cloud STT, set up Application Default Credentials. For more information, see Set up authentication for a local development environment.

import os

from google.cloud.speech_v2 import SpeechClient
from google.cloud.speech_v2.types import cloud_speech

PROJECT_ID = os.getenv("GOOGLE_CLOUD_PROJECT")


def transcribe_word_time_offsets_v2(
    audio_file: str,
) -> cloud_speech.RecognizeResponse:
    """Transcribes an audio file into text using with word time offsets.
    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
            with word time offsets.
    """
    # Instantiates a client
    client = SpeechClient()

    # Reads a file as bytes
    with open(audio_file, "rb") as file:
        audio_content = file.read()

    config = cloud_speech.RecognitionConfig(
        auto_decoding_config=cloud_speech.AutoDetectDecodingConfig(),
        language_codes=["en-US"],
        model="long",
        features=cloud_speech.RecognitionFeatures(
            enable_word_time_offsets=True,
        ),
    )

    request = cloud_speech.RecognizeRequest(
        recognizer=f"projects/{PROJECT_ID}/locations/global/recognizers/_",
        config=config,
        content=audio_content,
    )

    # Transcribes the audio into text
    response = client.recognize(request=request)

    for result in response.results:
        print(f"Transcript: {result.alternatives[0].transcript}")

    return response

What's next

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