Speechace
SpeechAce teaches correct American English pronunciation and eliminates your accent one word at a time.
Integrate the Speechace API with the Python API
Setup the Speechace API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Speechace and Python remarkably fast. Free for developers.
Popular Speechace and Python Actions#
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Overview of Speechace#
The Speechace API offers capabilities for detailed speech analysis, particularly useful for language learning applications. With this API, you can assess users' pronunciation and fluency in English by analyzing audio inputs. In Pipedream, you can leverage this API to craft workflows that trigger on various events, process audio data, and perform actions based on the analysis—such as storing results, providing feedback, or integrating with other services for enhanced functionality.
Connect Speechace#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
speechace: {
type: "app",
app: "speechace",
}
},
async run({steps, $}) {
return await axios($, {
method: "post",
url: `https://api.speechace.co/api/validating/text/v9/json`,
params: {
key: `${this.speechace.$auth.product_key}`,
dialect: `en-us`,
text: `Welcome to the world of workflow automation.`,
},
})
},
})
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}}