How to connect Google Cloud Speech-To-Text and Miro
Create a New Scenario to Connect Google Cloud Speech-To-Text and Miro
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 Miro will be your first step. To do this, click "Choose an app," find Google Cloud Speech-To-Text or Miro, 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.

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

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Authenticate Miro
Now, click the Miro node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Miro settings. Authentication allows you to use Miro through Latenode.
Configure the Google Cloud Speech-To-Text and Miro Nodes
Next, configure the nodes by filling in the required parameters according to your logic. Fields marked with a red asterisk (*) are mandatory.
Set Up the Google Cloud Speech-To-Text and Miro 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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AI Anthropic Claude 3
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Trigger on Webhook
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Save and Activate the Scenario
After configuring Google Cloud Speech-To-Text, Miro, 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 Miro integration works as expected. Depending on your setup, data should flow between Google Cloud Speech-To-Text and Miro (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 Miro
Google Cloud Speech-To-Text + Miro + Slack: When a long audio file is processed by Google Cloud Speech-To-Text, the resulting transcript is added to a specified Miro board. Then, a summary of the transcript is sent to a designated Slack channel.
Miro + Google Cloud Speech-To-Text + Google Docs: When a new board is created in Miro, its audio recordings are extracted and sent to Google Cloud Speech-To-Text for transcription. The transcribed text is then compiled into a new Google Document.
Google Cloud Speech-To-Text and Miro 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.
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About Miro
Automate Miro board updates based on triggers from other apps. Latenode connects Miro to your workflows, enabling automatic creation of cards, text, or frames. Update Miro based on data from CRMs, databases, or project management tools, reducing manual work. Perfect for agile project tracking and visual process management, inside fully automated scenarios.
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FAQ Google Cloud Speech-To-Text and Miro
How can I connect my Google Cloud Speech-To-Text account to Miro using Latenode?
To connect your Google Cloud Speech-To-Text account to Miro 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 Miro accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I transcribe meeting audio to Miro sticky notes?
Yes, you can! Latenode's advanced automation lets you convert audio from Google Cloud Speech-To-Text into Miro sticky notes, making collaboration and knowledge sharing seamless and efficient.
What types of tasks can I perform by integrating Google Cloud Speech-To-Text with Miro?
Integrating Google Cloud Speech-To-Text with Miro allows you to perform various tasks, including:
- Automatically add transcribed meeting notes as Miro sticky notes.
- Create Miro mind maps from spoken brainstorming sessions.
- Generate visual summaries of customer feedback from audio recordings.
- Collaboratively edit transcribed audio content directly in Miro.
- Analyze speech data and visualize insights on Miro boards.
How does Latenode handle Google Cloud Speech-To-Text API authentication?
Latenode securely manages Google Cloud Speech-To-Text API credentials using encrypted storage and provides a user-friendly authentication flow.
Are there any limitations to the Google Cloud Speech-To-Text and Miro integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large audio files may take longer to process due to API limits.
- Miro board size limits may affect the number of elements created.
- Accuracy of transcription depends on audio quality and language.