Generative AI for Video Translation: A Scalable Architecture for Multilingual Video Conferencing

• URL: http://arxiv.org/abs/2512.13904v1
• Date: Mon, 15 Dec 2025 21:21:09 GMT
• Title: Generative AI for Video Translation: A Scalable Architecture for Multilingual Video Conferencing
• Authors: Amirkia Rafiei Oskooei, Eren Caglar, Ibrahim Sahin, Ayse Kayabay, Mehmet S. Aktas,
• Abstract summary: Real-time deployment of cascaded generative AI pipelines for applications like video translation is constrained by significant system-level challenges.<n>This paper proposes and evaluates a practical system-level framework designed to mitigate these critical bottlenecks.<n>The proposed architecture incorporates a turn-taking mechanism to reduce computational complexity from quadratic to linear in multi-user scenarios.
• Score: 0.21748200848556343
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The real-time deployment of cascaded generative AI pipelines for applications like video translation is constrained by significant system-level challenges. These include the cumulative latency of sequential model inference and the quadratic ($\mathcal{O}(N^2)$) computational complexity that renders multi-user video conferencing applications unscalable. This paper proposes and evaluates a practical system-level framework designed to mitigate these critical bottlenecks. The proposed architecture incorporates a turn-taking mechanism to reduce computational complexity from quadratic to linear in multi-user scenarios, and a segmented processing protocol to manage inference latency for a perceptually real-time experience. We implement a proof-of-concept pipeline and conduct a rigorous performance analysis across a multi-tiered hardware setup, including commodity (NVIDIA RTX 4060), cloud (NVIDIA T4), and enterprise (NVIDIA A100) GPUs. Our objective evaluation demonstrates that the system achieves real-time throughput ($τ< 1.0$) on modern hardware. A subjective user study further validates the approach, showing that a predictable, initial processing delay is highly acceptable to users in exchange for a smooth, uninterrupted playback experience. The work presents a validated, end-to-end system design that offers a practical roadmap for deploying scalable, real-time generative AI applications in multilingual communication platforms.

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