Autopod: An AI-Driven Framework for Automated Podcast Production and Optimization

Abstract

Podcasting has become a widely adopted medium for communication, education, and entertainment. However, the traditional podcast production process remains resource-intensive, requiring significant manual effort and technical expertise. This paper introduces Autopod, an AI-powered podcast studio designed to automate and optimize podcast production. Leveraging advanced artificial intelligence, Autopod performs tasks such as audio enhancement, multi-speaker recognition, transcription, episode structuring, and metadata generation. The system reduces production time while improving content quality, making it accessible to both amateur creators and professional media organizations. Experimental results demonstrate Autopod's effectiveness in enhancing audio clarity, improving transcription accuracy, and significantly reducing editing time. This study presents the system’s methodology, evaluation, and potential impact on digital content creation.