The artificial intelligence behind the podcast microphone: AI-generated content in podcasting

Abstract

This paper presents a comprehensive literature review, the main aim of which is to gather information on the ways in which artificial intelligence is currently being used in content generation in the podcast industry, what tools can be used to do so, and how the merging of the two fields has evolved. Based on the structure and role specification of the podcast host, AI tools that could fulfill these roles were identified. The paper specifically focuses on podcast production in the early stages, i.e. the conception, development and curation of raw content, for which advanced technologies for Automatic Speech Recognition (ASR), Speech Synthesis (TTS) and Generative Pre-trained Transformer (GPT) are specific. This review is based on systematic research in databases, academic journals, conference proceedings, and other relevant sources related to artificial intelligence, the podcasting industry, and a generalization of their results. In particular, the Google Scholar database for scholarly articles and Google search engines were used to collect information on these tools. Finally, individual research on AI-generated content in the time range between 2006 – 2023 was construed using a neutral interpretation. The final selection includes 14 relevant studies in the field of AI and podcasting interfacing and 48 selected AI tools that can mostly be used individually and separately in the entire podcast production process. The contribution of this literature review is the structured consolidation of information, promotion of interdisciplinary research, and provision of state of the art in the field.