AI AND MACHINE LEARNING IN AUDIO-VISUAL MEDIA PRODUCTION: INTELLIGENT CONTENT CREATION, EDITING AND AUDIENCE ANALYTICS
DOI:
https://doi.org/10.29121/shodhkosh.v7.i5s.2026.7804Keywords:
Artificial Intelligence, Machine Learning, Audio-Visual Media, Content Creation, Video Editing, Audience AnalyticsAbstract [English]
Artificial Intelligence (AI) and Machine Learning (ML) are increasingly redefining the paradigms of audio-visual media production by enabling intelligent content creation, automated editing, and data-driven audience analytics. This paper explores the transformative role of AI-driven technologies across the entire media production pipeline, including pre-production planning, generative content synthesis, post-production automation, and personalized content delivery. Advanced techniques such as deep learning, generative adversarial networks, and diffusion models facilitate high-quality video generation, sound enhancement, and real-time editing, thereby significantly reducing production time and cost. Furthermore, AI-powered analytics provide actionable insights into audience behavior, sentiment, and engagement patterns, enabling targeted storytelling and optimized content distribution strategies. While these advancements enhance creativity and efficiency, they also introduce critical challenges related to ethical concerns, intellectual property, bias, and content authenticity. This study presents a comprehensive academic perspective on the integration of AI and ML in audio-visual media, highlighting both technological innovations and socio-cultural implications. The findings emphasize the necessity for balanced adoption, combining human creativity with machine intelligence to achieve sustainable and responsible media production ecosystems.
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