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How to connect Google Cloud Speech-To-Text and Google Vertex AI
Create a New Scenario to Connect Google Cloud Speech-To-Text and Google Vertex AI
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 Google Vertex AI will be your first step. To do this, click "Choose an app," find Google Cloud Speech-To-Text or Google Vertex AI, 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.
Add the Google Vertex AI Node
Next, click the plus (+) icon on the Google Cloud Speech-To-Text node, select Google Vertex AI from the list of available apps, and choose the action you need from the list of nodes within Google Vertex AI.
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Authenticate Google Vertex AI
Now, click the Google Vertex AI node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your Google Vertex AI settings. Authentication allows you to use Google Vertex AI through Latenode.
Configure the Google Cloud Speech-To-Text and Google Vertex AI 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 Google Vertex AI 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, Google Vertex AI, 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 Google Vertex AI integration works as expected. Depending on your setup, data should flow between Google Cloud Speech-To-Text and Google Vertex AI (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 Google Vertex AI
Google Cloud Speech-To-Text + Google Vertex AI + Google Docs: Transcribes audio files stored in storage using Google Cloud Speech-To-Text (Async). It then analyzes the transcript's sentiment with Google Vertex AI's Gemini model and creates a Google Docs document summarizing the audio and sentiment analysis.
Google Cloud Speech-To-Text + Google Vertex AI + Slack: Transcribes audio files from storage using Google Cloud Speech-To-Text. The transcript is then summarized using Google Vertex AI, and the summary is sent as a message to a designated Slack channel.
Google Cloud Speech-To-Text and Google Vertex AI 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 Google Vertex AI
Use Vertex AI in Latenode to build AI-powered automation. Quickly integrate machine learning models for tasks like sentiment analysis or image recognition. Automate data enrichment or content moderation workflows without complex coding. Latenode’s visual editor makes it easier to chain AI tasks and scale them reliably, paying only for the execution time of each flow.
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FAQ Google Cloud Speech-To-Text and Google Vertex AI
How can I connect my Google Cloud Speech-To-Text account to Google Vertex AI using Latenode?
To connect your Google Cloud Speech-To-Text account to Google Vertex AI 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 Google Vertex AI accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I analyze call center conversations with Vertex AI?
Yes, you can! Latenode enables automated transcription and analysis. Get valuable insights from customer interactions using no-code and prompt-based AI.
What types of tasks can I perform by integrating Google Cloud Speech-To-Text with Google Vertex AI?
Integrating Google Cloud Speech-To-Text with Google Vertex AI allows you to perform various tasks, including:
- Automating sentiment analysis of transcribed audio data.
- Summarizing long audio recordings into concise text summaries.
- Classifying audio content based on identified keywords and themes.
- Generating insights from customer service call transcripts.
- Creating AI-powered chatbots that understand voice inputs.
How secure is my Google Cloud Speech-To-Text data in Latenode workflows?
Latenode employs industry-standard security practices, ensuring your data is protected during processing and transit within workflows.
Are there any limitations to the Google Cloud Speech-To-Text and Google Vertex AI integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large audio files may require significant processing time.
- Advanced Vertex AI features require a paid Vertex AI subscription.
- The accuracy of speech transcription depends on audio quality.
