Try Gemini 1.5 Pro, our most advanced multimodal model in Vertex AI, and see what you can build with a 1M token context window. Try Gemini 1.5 Pro, our most advanced multimodal model in Vertex AI, and see what you can build with a 1M token context window.

Use a custom endpoint with the Speech-to-Text API

This sample shows you how to use a custom endpoint with the Speech-to-Text API. This can be useful if you want to use a Speech-to-Text API endpoint that is located in a different region than your application.

Code sample

Python

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

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


# Pass an additional argument, ClientOptions, to specify the new endpoint.
_client_options = client_options.ClientOptions(
    api_endpoint="eu-speech.googleapis.com"
)

client = speech.SpeechClient(client_options=_client_options)

What's next

To search and filter code samples for other Google Cloud products, see the Google Cloud sample browser.