PodLingo AI – Automatic Podcast Transcription & Translation

Inspiration

Podcasts and interview-based content are growing rapidly across the internet, but most of this content is only accessible to people who understand the original spoken language. Many creators also struggle to add captions manually, which can take hours for a single episode.

What it does

We were inspired to build a solution that could demonstrate how artificial intelligence can simplify this process. Our goal was to explore how AI can automatically generate captions and translations for audio or video content, making podcasts easier to understand for global audiences.

PodLingo AI was created to show how intelligent captioning systems can help creators improve accessibility, reach more viewers, and make content more inclusive.

How we built it

The project was built using a modern web development stack focused on simplicity and usability.

Frontend:

React

Tailwind CSS

JavaScript

Backend:

Node.js

Express.js

Development tools:

VS Code

Local AI experimentation with Ollama

The platform allows users to upload and play audio or video content inside the browser. A caption synchronization system displays subtitles based on playback time so that captions appear automatically while the media plays.

The interface was designed to be simple and intuitive so users can quickly upload content and view captions without complicated steps.

Challenges we ran into

One of the main challenges was synchronizing captions with the media playback. The subtitles need to appear exactly at the right moment while the audio is playing, which required implementing a timestamp-based caption system.

Another challenge was designing the system in a way that demonstrates how AI-powered captioning would work without relying on heavy cloud infrastructure during development.

We solved this by creating a prototype system that simulates the behavior of an AI caption generator while maintaining the structure needed for future AI integration.