How to connect AI: Text-To-Speech and OCR Space
Create a New Scenario to Connect AI: Text-To-Speech and OCR Space
In the workspace, click the βCreate New Scenarioβ button.

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

Add the AI: Text-To-Speech Node
Select the AI: Text-To-Speech node from the app selection panel on the right.

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

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Authenticate OCR Space
Now, click the OCR Space node and select the connection option. This can be an OAuth2 connection or an API key, which you can obtain in your OCR Space settings. Authentication allows you to use OCR Space through Latenode.
Configure the AI: Text-To-Speech and OCR Space 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 AI: Text-To-Speech and OCR Space 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 donβt 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 AI: Text-To-Speech, OCR Space, and any additional nodes, donβt 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 βRun onceβ and triggering an event to check if the AI: Text-To-Speech and OCR Space integration works as expected. Depending on your setup, data should flow between AI: Text-To-Speech and OCR Space (or vice versa). Easily troubleshoot the scenario by reviewing the execution history to identify and fix any issues.
Most powerful ways to connect AI: Text-To-Speech and OCR Space
OCR Space + AI: Text-To-Speech + Google Drive: When a new file is added to a specified Google Drive folder, OCR Space converts the image to text. AI Text-To-Speech then generates an audio file from the extracted text, which is uploaded back to Google Drive.
OCR Space + AI: Text-To-Speech + Email: OCR Space converts text from an image. AI Text-To-Speech turns the text into speech. Email sends the audio file as an attachment.
AI: Text-To-Speech and OCR Space integration alternatives
About AI: Text-To-Speech
Automate voice notifications or generate audio content directly within Latenode. Convert text from any source (CRM, databases, etc.) into speech for automated alerts, personalized messages, or content creation. Latenode streamlines text-to-speech workflows and eliminates manual audio tasks, integrating seamlessly with your existing data and apps.
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About OCR Space
Need to extract text from images or PDFs? Use OCR Space in Latenode to automatically process documents and integrate the data into your workflows. Automate invoice processing, data entry, or compliance checks. Latenode adds flexible logic, file parsing, and destinations to your OCR results, scaling beyond single-document processing.
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FAQ AI: Text-To-Speech and OCR Space
How can I connect my AI: Text-To-Speech account to OCR Space using Latenode?
To connect your AI: Text-To-Speech account to OCR Space on Latenode, follow these steps:
- Sign in to your Latenode account.
- Navigate to the integrations section.
- Select AI: Text-To-Speech and click on "Connect".
- Authenticate your AI: Text-To-Speech and OCR Space accounts by providing the necessary permissions.
- Once connected, you can create workflows using both apps.
Can I automate audio creation from scanned documents?
Yes, you can! Latenode lets you seamlessly convert scanned documents from OCR Space into audio using AI: Text-To-Speech, automating content accessibility with a no-code visual builder.
What types of tasks can I perform by integrating AI: Text-To-Speech with OCR Space?
Integrating AI: Text-To-Speech with OCR Space allows you to perform various tasks, including:
- Automatically generating audiobooks from scanned book pages.
- Creating voiceovers for videos from document scripts.
- Converting scanned meeting notes into easily shareable audio summaries.
- Making archived documents accessible via audio transcription.
- Generating audio versions of scanned articles for visually impaired users.
How do I handle errors in my AI: Text-To-Speech Latenode workflows?
Latenode provides robust error handling. Use "Error" output ports and conditional logic to manage exceptions, ensuring stable automation.
Are there any limitations to the AI: Text-To-Speech and OCR Space integration on Latenode?
While the integration is powerful, there are certain limitations to be aware of:
- Large document processing might take longer depending on API usage limits.
- AI: Text-To-Speech supports limited languages and voices; check the services for specifics.
- OCR Space accuracy varies depending on image quality and document complexity.