Transcribe audio with model selection (v2)

Transcribe an audio file using the Speech-to-Text API with model selection.

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. 

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

# Instantiates a client
client = SpeechClient()

# TODO (Developer): Update the PROJECT_ID to the value of your project
# PROJECT_ID = "your-project-id"

# Reads a file as bytes
with open("resources/audio.wav", "rb") as f:
    audio_content = f.read()

config = cloud_speech.RecognitionConfig(
    auto_decoding_config=cloud_speech.AutoDetectDecodingConfig(),
    language_codes=["en-US"],
    model="short",  # Chosen model
)

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}")

What's next

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