标题： 它会是什么样的声音？ 面向室内场景的材料控制多模态声学轮廓生成 显示英文标题

标题： How Would It Sound? Material-Controlled Multimodal Acoustic Profile Generation for Indoor Scenes

摘要： 在有地毯地板和墙上有吸音板的录音室中，声音会如何变化？ 我们引入了材料控制的声学轮廓生成任务，其中给定一个具有特定视听特征的室内场景，目标是在推理时根据用户定义的材料配置生成目标声学轮廓。 我们采用一种新的编码器-解码器方法来解决这个问题，该方法从视听观察中编码场景的关键属性，并根据用户提供的材料规范生成目标房间冲激响应（RIR）。 我们的模型能够根据在推理时动态定义的各种材料配置生成多样化的RIR。 为了支持这项任务，我们创建了一个新的基准数据集，即声学奇境数据集，该数据集旨在在多样且具有挑战性的环境下开发和评估材料感知的RIR预测方法。 我们的结果表明，所提出的模型能够有效编码材料信息并生成高保真RIR，优于多个基线和最先进方法。 显示英文摘要

摘要： How would the sound in a studio change with a carpeted floor and acoustic tiles on the walls? We introduce the task of material-controlled acoustic profile generation, where, given an indoor scene with specific audio-visual characteristics, the goal is to generate a target acoustic profile based on a user-defined material configuration at inference time. We address this task with a novel encoder-decoder approach that encodes the scene's key properties from an audio-visual observation and generates the target Room Impulse Response (RIR) conditioned on the material specifications provided by the user. Our model enables the generation of diverse RIRs based on various material configurations defined dynamically at inference time. To support this task, we create a new benchmark, the Acoustic Wonderland Dataset, designed for developing and evaluating material-aware RIR prediction methods under diverse and challenging settings. Our results demonstrate that the proposed model effectively encodes material information and generates high-fidelity RIRs, outperforming several baselines and state-of-the-art methods.