Voice AI is capable of generating human language messages through deep learning algorithms, such as convolutional neural networks (CNN), which learn to imitate vocal patterns from speech data. In this context, the main objective is to provide an overview of voice AI applied to podcasting, aiming to answer whether the current technological offerings pose a threat to audio professionals’ jobs, particularly voice-over artists. To this end, the main software used by podcast creators for voice cloning is analyzed, and a comparative framework is established. Secondly, creators’ perceptions of the results are gathered by analyzing 10 titles. The main software provides specific tools that can enhance workflow and optimize production costs. Based on the findings about the current state of voice AI in podcasting, we have identified both the opportunities and limitations this technology offers to creators. It is observed that the voice AI industry is adapting to the sector’s needs, offering multiple tools through specialized platforms that allow for voice cloning, editing recordings, publishing podcasts, and distributing them in several languages. However, it is not perceived as an immediate threat due to the reproduction of inaccurate prosody and the absence of paralinguistic elements.
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