Google Cloud Speech-To-Text and Docparser Integration

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Automate document data extraction: use Google Cloud Speech-To-Text to transcribe audio, then Docparser to structure text into usable data. Latenode allows adding custom JavaScript logic and scales affordably.

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Google Cloud Speech-To-Text

Docparser

Step 1: Choose a Trigger

Step 2: Choose an Action

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How to connect Google Cloud Speech-To-Text and Docparser

Create a New Scenario to Connect Google Cloud Speech-To-Text and Docparser

In the workspace, click the “Create New Scenario” button.

Add the First Step

Add the first node – a trigger that will initiate the scenario when it receives the required event. Triggers can be scheduled, called by a Google Cloud Speech-To-Text, triggered by another scenario, or executed manually (for testing purposes). In most cases, Google Cloud Speech-To-Text or Docparser will be your first step. To do this, click "Choose an app," find Google Cloud Speech-To-Text or Docparser, and select the appropriate trigger to start the scenario.

Add the Google Cloud Speech-To-Text Node

Select the Google Cloud Speech-To-Text node from the app selection panel on the right.

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Configure the Google Cloud Speech-To-Text

Click on the Google Cloud Speech-To-Text node to configure it. You can modify the Google Cloud Speech-To-Text URL and choose between DEV and PROD versions. You can also copy it for use in further automations.

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Add the Docparser Node

Next, click the plus (+) icon on the Google Cloud Speech-To-Text node, select Docparser from the list of available apps, and choose the action you need from the list of nodes within Docparser.

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Authenticate Docparser

Now, click the Docparser node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Docparser settings. Authentication allows you to use Docparser through Latenode.

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Configure the Google Cloud Speech-To-Text and Docparser Nodes

Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.

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Set Up the Google Cloud Speech-To-Text and Docparser Integration

Use various Latenode nodes to transform data and enhance your integration:

  • Branching: Create multiple branches within the scenario to handle complex logic.
  • Merging: Combine different node branches into one, passing data through it.
  • Plug n Play Nodes: Use nodes that don’t require account credentials.
  • Ask AI: Use the GPT-powered option to add AI capabilities to any node.
  • Wait: Set waiting times, either for intervals or until specific dates.
  • Sub-scenarios (Nodules): Create sub-scenarios that are encapsulated in a single node.
  • Iteration: Process arrays of data when needed.
  • Code: Write custom code or ask our AI assistant to do it for you.
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Save and Activate the Scenario

After configuring Google Cloud Speech-To-Text, Docparser, and any additional nodes, don’t forget to save the scenario and click "Deploy." Activating the scenario ensures it will run automatically whenever the trigger node receives input or a condition is met. By default, all newly created scenarios are deactivated.

Test the Scenario

Run the scenario by clicking “Run once” and triggering an event to check if the Google Cloud Speech-To-Text and Docparser integration works as expected. Depending on your setup, data should flow between Google Cloud Speech-To-Text and Docparser (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.

Most powerful ways to connect Google Cloud Speech-To-Text and Docparser

Google Cloud Speech-To-Text + Docparser + Google Sheets: Transcribe audio from cloud storage using Google Cloud Speech-To-Text, then extract structured data from the transcribed text using Docparser. Finally, add the parsed data as a new row to a Google Sheet.

Google Cloud Speech-To-Text + Docparser + Salesforce: When audio is available in cloud storage, transcribe it using Google Cloud Speech-To-Text. Parse information from the transcribed text using Docparser and then update an existing record in Salesforce with the extracted data.

Google Cloud Speech-To-Text and Docparser integration alternatives

About Google Cloud Speech-To-Text

Automate audio transcription using Google Cloud Speech-To-Text within Latenode. Convert audio files to text and use the results to populate databases, trigger alerts, or analyze customer feedback. Latenode provides visual tools to manage the flow, plus code options for custom parsing or filtering. Scale voice workflows without complex coding.

About Docparser

Extract data from PDFs, invoices, and forms automatically with Docparser in Latenode. Stop manual data entry. Build workflows that trigger actions based on parsed content. Use Latenode’s no-code tools to filter, transform, and route data to your database or apps, creating scalable document processing pipelines.

See how Latenode works

FAQ Google Cloud Speech-To-Text and Docparser

How can I connect my Google Cloud Speech-To-Text account to Docparser using Latenode?

To connect your Google Cloud Speech-To-Text account to Docparser on Latenode, follow these steps:

  • Sign in to your Latenode account.
  • Navigate to the integrations section.
  • Select Google Cloud Speech-To-Text and click on "Connect".
  • Authenticate your Google Cloud Speech-To-Text and Docparser accounts by providing the necessary permissions.
  • Once connected, you can create workflows using both apps.

Can I automate data extraction from transcribed audio files?

Yes, with Latenode! Automatically transcribe audio with Google Cloud Speech-To-Text, then use Docparser to extract key data. Latenode's flexible workflow lets you process large volumes easily.

What types of tasks can I perform by integrating Google Cloud Speech-To-Text with Docparser?

Integrating Google Cloud Speech-To-Text with Docparser allows you to perform various tasks, including:

  • Automatically extract data from dictated reports and store them.
  • Process customer support call transcripts for sentiment analysis.
  • Analyze voice meeting records and extract key discussion points.
  • Convert audio invoices to text, then parse amounts and due dates.
  • Automate processing of voice memos and generate structured data.

What level of transcription accuracy can I expect on Latenode?

Accuracy depends on audio quality and Google Cloud Speech-To-Text settings. Latenode handles the data flow so you can focus on optimization.

Are there any limitations to the Google Cloud Speech-To-Text and Docparser integration on Latenode?

While the integration is powerful, there are certain limitations to be aware of:

  • Large audio files may require significant processing time.
  • Docparser's parsing accuracy depends on document structure.
  • Complex workflows may require JavaScript knowledge.

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