Turn Blog Posts into Searchable Audio with AI

This blog post provides a detailed, step-by-step guide on using Nocodo.ai to convert written blog posts into audio files and make them searchable through AI-powered functionality. It covers setting up API input nodes to capture text, configuring AWS Polly for text-to-speech conversion, managing AWS credentials, storing audio files using cloud services, and implementing text embedding for AI searchability. The guide aims to help users enhance content accessibility and audience engagement by transforming blog posts into searchable audio formats.

A modern desk setup with a laptop displaying a blog post. From the laptop screen, an audio waveform emerges, symbolizing the conversion of text to audio. On the desk, there are headphones and a microphone, representing audio recording and playback. The background features natural lighting, giving the scene a professional and engaging atmosphere.
Tanja BayerFunko Pop figure of a Tanja with brown hair, wearing a red jacket, holding a mug and a tablet, with a badge around their neck.

Tanja Bayer

3 min read
In an era where content consumption preferences vary widely among audiences, making your blog posts accessible in multiple formats can significantly boost your reach and engagement. With Nocodo AI, you can easily transform your written blog posts into audio files and make them searchable through AI-powered search functionality. Follow this detailed, step-by-step guide to set up a workflow in Nocodo AI that automates the entire process, ensuring your content is more accessible and discoverable.
Flowchart with interconnected nodes on a dark background, displaying text boxes and lines indicating relationships.

Prepare Your Blog Post

Step 1: Create Your Blog Post
Ensure your blog post is well-written and formatted. This is crucial as the text quality directly affects the speech synthesis quality.
Step 2: Access Nocodo AI
Log in to your Nocodo AI account. If you do not have an account, you can sign up for a new one effortlessly.

Setting Up the API Input Node

User interface showing a POST Data Input with an option to add API input fields. One field labeled "blogpost" is set to "Text."
Step 1: Initialize a New Project
Once logged in, start a new project by selecting the option to create a new stack or project.
Step 2: Configure the POST Data Input Node
Drag the "POST Data Input" node into your project. This node will capture the text of your blog post from an incoming POST request. Configure it to extract the blog post text by defining dynamic output anchors.

Configure AWS Polly for Text-to-Speech

Screenshot of a configuration interface for AWS services, including fields for AWS Region, Access Key, Secret Access Key, and Polly voice settings.
Step 1: Set Up AWS Config Node
Add an "AWS Config" node to provide AWS credentials. Input your AWS Access Key ID, Secret Access Key, and region. This configuration is necessary for accessing AWS services like Polly.
Step 2: Add AWS Polly Node
Place the "AWS Polly" node into your stack. Link it to the output of your "POST Data Input" node, ensuring it receives the blog post text. Configure Polly to convert the text into speech by selecting your desired voice and output format (e.g., MP3).

Output the Audio File

UI for a file writer utility showing AWS S3 as the storage provider, with fields for file path, bucket name, and AWS config.
Step 1: Configure the File Writer Node
After the audio file is generated by Polly, add a "File Writer" node to your workflow. Set this node to upload the audio file to your preferred cloud storage service, such as AWS S3, specifying the file path and bucket name.

Make Your Content Searchable

Flowchart with interconnected nodes labeled "AWS Config," "OpenSearch Client," "AWS Rekognition," "Vector Store Writer," and "Vector Store Reader."
Step 1: Set Up Text Embedding
Introduce an "AWS Bedrock Embedder" node to generate embeddings of your blog post text, which help in making the content searchable.
Step 2: Store and Index Embeddings
Use the "Vector Store" node to interface with your database client and store the generated embeddings.
Step 3: Implement the Search Functionality
Add a "Vector Store Reader" node to retrieve search results based on the embeddings. This node will allow your audio content to be searchable by AI, enhancing its discoverability.

Save and Execute Your Workflow

With all nodes configured and connected, save your workflow. You can then execute it by clicking the 'Execute' button, turning your blog post into an accessible audio file and making it searchable through AI-powered functionality.

Conclusion

By utilizing Nocodo AI to convert and index your blog posts as audio files, you not only cater to a broader audience but also enhance user engagement through accessible and searchable content. Start using Nocodo AI today to transform how your audience interacts with your content.

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