Integrate the Azure Speech Service API with the Python API

Setup the Azure Speech Service API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Azure Speech Service and Python remarkably fast. Free for developers.

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Popular Azure Speech Service and Python Actions#

Run Python Code with the Python API

Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.

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Overview of Azure Speech Service#

The Azure Speech Service API offers a suite of speech-to-text, text-to-speech, and speech translation capabilities, allowing you to integrate advanced speech processing into your applications. With the API, you can transcribe audio into text, convert text into natural-sounding speech, and even translate spoken languages in real-time. Leveraging these features within Pipedream, you can automate workflows that respond to voice commands, generate audio content from textual data, or provide real-time translation services for global communication.

Connect Azure Speech Service#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    azure_speech_service: {
      type: "app",
      app: "azure_speech_service",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `${this.azure_speech_service.$auth.endpoint}/speechtotext/v3.1/healthstatus`,
      headers: {
        "Ocp-Apim-Subscription-Key": `${this.azure_speech_service.$auth.api_key}`,
      },
    })
  },
})

Overview of Python#

Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.

This includes installing PyPI packages, within your code without having to manage a requirements.txt file or running pip.

Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:

Connect Python#

def handler(pd: "pipedream"):
  # Reference data from previous steps
  print(pd.steps["trigger"]["context"]["id"])
  # Return data for use in future steps
  return {"foo": {"test":True}}

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