PaperToPodcast

ResearchContent creationOpen Source

What is PaperToPodcast?

Paper-to-Podcast is a tool designed to transform academic research papers into engaging, conversational podcasts. By simulating a three-person discussion with distinct personas—Host, Learner, and Expert—it makes complex information more accessible and enjoyable for listeners. The project uses AI-driven chains for planning, discussion generation, and script refinement, ensuring accuracy and flow while maintaining cost efficiency through OpenAI's API.

Features

Transforms PDF research papers into conversational podcasts

Simulates discussions with three distinct personas

Utilizes retrieval-augmented generation for accurate content

Refines scripts for smooth transitions and flow

Supports OpenAI API for realistic text-to-speech voices

Links

Website

Pros and Cons of PaperToPodcast

Pros

Makes academic content more accessible and engaging

Cost-effective, with low API usage costs

Provides structured insights through persona-based discussions

Ensures accuracy with retrieval-augmented models

Offers flexibility for future local LLM and TTS integration

Cons

Current runtime may be slow for longer papers

Dependent on OpenAI API for now

Requires technical setup for local use

Limited to English language support currently

Optimization and local implementation still in progress

PaperToPodcast Use Cases

Converting research papers for commuters or travelers

Enhancing learning through conversational formats

Creating educational content for students and researchers

Generating podcasts for academic or professional training

Exploring open-source alternatives for cost-free implementations

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