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How are being used artificial intelligence technologies in radio production? 


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Artificial intelligence (AI) technologies are revolutionizing radio production by enhancing various aspects. In China, AI has been pivotal in the broadcasting industry since 2000, with a focus on audience engagement and content personalization . Cognitive radio networks utilize AI techniques like artificial neural networks and rule-based systems to optimize spectrum usage and enhance responsiveness and security . AI in radio and television planning involves content production, editing, and smart distribution, improving information communication and audience engagement . Additionally, AI aids in content creation, post-production, audience analytics, and accessibility in the media sector, including radio, by automating tasks like transcription, translation, and content recommendation . These applications of AI in radio production not only increase efficiency but also enable personalized content delivery and improved audience interaction.

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Proceedings ArticleDOI
12 Oct 2020
AI in radio production involves AI applications in content creation, editing, audience analytics, and accessibility enhancements like transcription and translation, improving efficiency and audience engagement in the radio broadcasting sector.
Artificial intelligence is utilized in radio production for automatic transcription and news segmentation, enhancing content accessibility and reusability across platforms, as demonstrated in the study on RNE.
Artificial intelligence in radio production aids in smart content creation, editing, recommendation, and distribution, enhancing audience engagement and optimizing news dissemination processes.
Artificial intelligence is utilized in Chinese radio broadcasting to enhance audience experience, competitiveness, and content diversity, promoting interaction and exploring new program styles for future development.
Artificial intelligence techniques like artificial neural networks, metaheuristic algorithms, rule-based systems, ontology-based systems, and case-based systems are utilized in cognitive radio networks for dynamic spectrum access and allocation.

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