PDF to Podcast Generator: Use AI to Convert Documents into Multi-Role Conversational Podcasts

The PDF to Podcast Generator is an open-source tool developed by utkarshP-11 (GitHub project), built on Streamlit. It combines large language models (LLMs) and text-to-speech (TTS) technology to automatically convert static PDF documents into multi-role conversational podcasts. It aims to address the pain point of limited reading time in the era of information explosion, allowing users to "listen" to documents during commutes and other scenarios.

In the era of information explosion, people are faced with massive documents, papers, and reports, but reading time is increasingly limited. This project targets this pain point by using AI technology to convert static PDF content into vivid audio dialogue forms, expanding new paths for content consumption.

The front end uses the Streamlit framework to quickly implement an interactive web application; LLMs are responsible for document parsing, content understanding, dialogue generation, and script optimization; multi-role design simulates real podcast discussions; TTS technology converts dialogues into speech, distinguishing between character voices.

Covers scenarios such as academic research (listening to papers during commutes), business reports (digesting analysis while exercising), educational learning (converting textbooks to podcasts to enhance memory), and accessible reading (assisting visually impaired or reading-impaired individuals).

Needs to solve problems such as PDF structure extraction (unstructured formats), dialogue quality control (converting academic text to natural dialogue), and naturalness of speech synthesis (multi-role intonation and emotion).

As an open-source project, it provides developers with opportunities to learn Streamlit for building AI applications, LLM content reconstruction, and multi-modal integration, and can be used as a basis to develop more professional tools.

Plans to expand multilingual support, allow users to customize voice styles, add interactive Q&A, and combine virtual avatars to generate video podcasts.

This project creatively uses AI to build a bridge between static documents and audio content, has practical value in the era of attention scarcity, and provides references and inspiration for knowledge workers and developers.