音乐驱动：面向车载体验的上下文感知生成音频

中文摘要 AI 辅助

车载音乐可作为自适应界面，用于提升驾驶员体验、注意力与健康状态。我们提出Drive-to-Music，这是一种基于多模态驾驶信号实时生成音乐的上下文感知系统。该系统利用行车记录仪图像与车辆遥测数据，提取场景语义与驾驶上下文，将其映射至高层音乐描述符，并对生成式音频模型进行条件约束，以生成与上下文匹配的音轨。该架构结合感知与生成组件，将视觉与运动输入转换为结构化音乐属性，且能以低延迟合成音频；支持驾驶条件变化时的平滑过渡，为确保鲁棒性与部署就绪性，我们在整个生成流程中融入基于约束的控制与安全检查。实验结果证明，在汽车场景下实现实时上下文感知音乐生成是可行的，为个性化与自适应车载音频体验奠定了基础。

英文摘要

In-vehicle music can serve as an adaptive interface to enhance driver experience, attention, and well-being. We present Drive-to-Music, a context-aware system that generates music in real time from multimodal driving signals. Using dashcam imagery and vehicle telemetry, the system extracts scene semantics and driving context, maps them to high-level musical descriptors, and conditions generative audio models to produce contextually aligned soundtracks. The architecture combines perception and generative components to translate visual and kinematic inputs into structured musical attributes and synthesize audio with low latency. It supports smooth transitions as driving conditions evolve, and to ensure robustness and deployment readiness, we incorporate constraint-based controls and safety checks across the generation pipeline. Our results demonstrate the feasibility of real-time, context-aware music generation in automotive settings, providing a foundation for personalized and adaptive in-vehicle audio experiences.

发表机构

• Mercedes-Benz Research & Development North America（梅赛德斯-奔驰北美研发中心）

机构由 AI 辅助整理，请以论文原文为准。