Long-Horizon Audio-Visual Generation for Persistent Stories and Interactive Worlds

📅 2026-08-24
📈 Citations: 0
Influential: 0
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🤖 AI Summary
研究解决了长视频和互动世界生成问题,通过引入JoyAI-Echo-1.5系统,利用跨镜头记忆、几何控制及自生成回放训练方法,提高了角色一致性、视觉质量和语音保真度。
📝 Abstract
Video generation is progressing beyond isolated clips toward long-form narratives and interactive worlds, requiring models to preserve identities, follow user controls, and remain stable over extended rollouts. We present JoyAI-Echo-1.5, a unified audio-visual generation system with two purpose-built variants. The long-video variant introduces composable cross-shot memory that aggregates visual evidence across multiple prior shots and speaker cues derived from speech-filtered full-shot audio, enabling persistent character appearance and voice identity across flexible combinations of text, image, and memory conditioning. The world-model variant converts heterogeneous navigation inputs into calibrated metric 6-DoF camera trajectories and injects them through a geometry-aware conditioning pathway, enabling controller-agnostic interaction across flexible viewpoints. To support efficient long-horizon generation, we transform a bidirectional audio-visual backbone into a causal few-step generator using progressive teacher forcing and short- and long-horizon Self-Gradient Forcing on self-generated rollouts. Experiments demonstrate strong performance in both settings. JoyAI-Echo-1.5 achieves improvements over existing long-video baselines in cross-shot consistency, visual quality, text alignment, and speech fidelity. Its world-model variant ranks first on WBench, with an average score of 81.7, and achieves leading visual quality and long-horizon persistence on SANA-WM-Bench. Together, these results indicate that memory, geometric control, and rollout-aware training provide a practical foundation for generating coherent stories and continuously evolving interactive worlds. Project page: https://echo-team-joy-future-academy-jd.github.io/Echo-1.5-Page/.
Problem

Research questions and friction points this paper is trying to address.

long-horizon
audio-visual generation
persistent stories
interactive worlds
cross-shot consistency
Innovation

Methods, ideas, or system contributions that make the work stand out.

composable cross-shot memory
geometry-aware conditioning pathway
causal few-step generator
Self-Gradient Forcing