In the fast-paced world of research, staying updated can be a challenge. The Research Paper to Podcast Converter is a Streamlit-based application that transforms academic PDFs into audio podcasts, making it easier for researchers to consume content on the go. This project leverages ChatGroq, TextBlob, and gTTS to extract, summarize, and convert text into speech, with optional sentiment-based voice adjustments and background music integration.
The tool can accurately extract text from PDF documents, preserving the original content's integrity. This is particularly useful for academic papers, reports, and other research documents that are often available in PDF format.
To make lengthy papers more digestible, the application offers an optional summarization feature. This feature condenses complex information into concise summaries without losing the essence of the original content. It is especially beneficial for researchers looking to grasp the main ideas quickly.
Understanding the sentiment of the content can enhance the listening experience. The tool analyzes the sentiment of the text (positive, neutral, or negative) and adjusts the tone and speed of the speech accordingly. This nuanced approach makes the audio more engaging and easier to follow.
The core of the application is its ability to convert text into natural-sounding speech. Users can listen to research papers as podcasts, making it easier to absorb information during commutes, workouts, or while multitasking.
To enhance the podcast's appeal, users can upload background music that is seamlessly integrated with the speech. This feature creates a more professional and enjoyable listening experience, akin to popular podcast formats.
The application is built using Streamlit, providing a clean and interactive user interface. Users can upload PDFs, choose to summarize the content, adjust sentiment settings, and even preview the generated podcasts directly on the platform.
Makes research accessible to visually impaired individuals or those who prefer auditory learning.
Facilitates information consumption during non-traditional reading times, such as while driving or exercising.
Summarization reduces the time required to understand lengthy papers.
Audio format allows users to learn passively, maximizing productivity.
Adjustable tone and background music cater to individual preferences.
Sentiment-based adjustments make the content more engaging and relatable.
The Research Paper to Podcast Converter is more than just a tool; it is a gateway to making knowledge more accessible and convenient. By transforming dense academic texts into easy-to-consume podcasts, it empowers users to stay informed and educated anytime, anywhere. As we look to the future, expanding language capabilities and refining the audio experience will remain top priorities to ensure this tool meets the evolving needs of its audience.
GitHub
https://github.com/AmanTiwari005/VoiceMyPaper/blob/main/test.py
There are no datasets linked
There are no models linked
There are no datasets linked
There are no models linked
