The Evolution and Aesthetic Reconstruction of the Expression Style of Broadcasting and Hosting in the Context of Integration

Huanqiu Zhang

GBP Proceedings Series, 2025, vol. 9, 25-31

Abstract: In the context of media convergence, the expression styles of broadcasting and hosting have undergone significant evolution, reflecting shifts in communication modes and audience expectations. This paper examines the dynamic transformation and aesthetic reconstruction of broadcasting expression, highlighting a transition from traditional standardized delivery to more authentic, interactive, and emotionally engaging styles. Drawing on insights from AI-powered language learning practices-such as intelligent feedback, contextual simulation, and prosody training-this study explores how emerging AI technologies inspire new paradigms for language competence and expressive flexibility in broadcasting. The integration of AI and media convergence not only enriches aesthetic standards but also presents novel opportunities and challenges for the future development of broadcasting expression.

Keywords: broadcasting expression; media convergence; aesthetic reconstruction; AI-assisted language learning; expression style evolution; multimodal communication (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:axf:gbppsa:v:9:y:2025:i::p:25-31

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