How to connect Google AI and Google Cloud Speech-To-Text
Create a New Scenario to Connect Google AI and Google Cloud Speech-To-Text
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 AI, triggered by another scenario, or executed manually (for testing purposes). In most cases, Google AI or Google Cloud Speech-To-Text will be your first step. To do this, click "Choose an app," find Google AI or Google Cloud Speech-To-Text, and select the appropriate trigger to start the scenario.

Add the Google AI Node
Select the Google AI node from the app selection panel on the right.

Google AI
Configure the Google AI
Click on the Google AI node to configure it. You can modify the Google AI URL and choose between DEV and PROD versions. You can also copy it for use in further automations.
Add the Google Cloud Speech-To-Text Node
Next, click the plus (+) icon on the Google AI node, select Google Cloud Speech-To-Text from the list of available apps, and choose the action you need from the list of nodes within Google Cloud Speech-To-Text.

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Authenticate Google Cloud Speech-To-Text
Now, click the Google Cloud Speech-To-Text node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Google Cloud Speech-To-Text settings. Authentication allows you to use Google Cloud Speech-To-Text through Latenode.
Configure the Google AI and Google Cloud Speech-To-Text 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 AI and Google Cloud Speech-To-Text 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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Trigger on Webhook
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Save and Activate the Scenario
After configuring Google AI, Google Cloud Speech-To-Text, 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 AI and Google Cloud Speech-To-Text integration works as expected. Depending on your setup, data should flow between Google AI and Google Cloud Speech-To-Text (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect Google AI and Google Cloud Speech-To-Text
Google Cloud Speech-To-Text + Google AI + Slack: Transcribe audio from storage using Google Cloud Speech-To-Text, analyze the transcribed text using Google AI to determine sentiment, and then post a summary of the audio and its sentiment analysis to a specified Slack channel for team review and action.
Slack + Google AI + Google Cloud Speech-To-Text: When a new file is added to a Slack channel, transcribe the audio in the file using Google Cloud Speech-To-Text and use Google AI to generate a summary, then post the summary back to the same Slack channel.
Google AI and Google Cloud Speech-To-Text integration alternatives
About Google AI
Use Google AI in Latenode to add smarts to your workflows. Process text, translate languages, or analyze images automatically. Unlike direct API calls, Latenode lets you combine AI with other apps, add logic, and scale without code. Automate content moderation, sentiment analysis, and more.
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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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See how Latenode works
FAQ Google AI and Google Cloud Speech-To-Text
How can I connect my Google AI account to Google Cloud Speech-To-Text using Latenode?
To connect your Google AI account to Google Cloud Speech-To-Text on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select Google AI and click on "Connect".
- Authenticate your Google AI and Google Cloud Speech-To-Text accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I transcribe audio, then analyze sentiment?
Yes, using Latenode, you can easily transcribe audio via Google Cloud Speech-To-Text, then use Google AI for sentiment analysis. Latenode's visual interface simplifies complex workflows.
What types of tasks can I perform by integrating Google AI with Google Cloud Speech-To-Text?
Integrating Google AI with Google Cloud Speech-To-Text allows you to perform various tasks, including:
- Transcribing customer service calls and analyzing agent performance.
- Automating meeting summaries with action item extraction.
- Creating voice-controlled applications with natural language understanding.
- Analyzing audio content for brand mentions and social sentiment.
- Generating written content from spoken words with AI refinement.
How secure is Google AI data within Latenode workflows?
Latenode uses secure data handling practices, encrypting sensitive information at rest and in transit. Your data remains protected throughout workflows.
Are there any limitations to the Google AI and Google Cloud Speech-To-Text integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large audio files may require significant processing time.
- Custom model training requires separate setup in Google AI.
- Integration is subject to Google AI and Google Cloud Speech-To-Text API usage limits.