Scalable Room Acoustic Modelling (SCReAM)

我们一生中大部分时间都在室内度过。在封闭的空间内，声音被多次反射，导致混响。我们习惯于感知回响——我们无意识地用它来导航空间，当它不在时，我们会注意到。同样，我们的电子设备，如笔记本电脑、电视或智能家居设备，都暴露在混响中，需要考虑它的存在。因此，能够预测、合成和控制混响是很重要的。这是通过室内声学模型完成的。现有的室内声学模型有两个主要的局限性。首先，它们最初是从非常不同的起点和非常不同的目的发展起来的，这导致了一个高度分散的研究领域，一个领域的进步并不能转化为其他领域的进步，从而减慢了研究速度。其次，每个模型都有特定的精度和特定的计算复杂性，一些非常精确的模型需要几天的时间来运行（物理模型），而另一些则是实时运行，但精度很低，只是为了创造一个令人愉悦的混响声音（感知模型）。因此，没有一个单一的模型可以允许从一个极端到另一个极端的连续缩放。该项目将通过定义一种新颖的、统一的房间声学模型来克服这两个限制，该模型结合了所有主要类型模型的吸引人的特性，并且可以根据需要从轻量级感知模型扩展到全尺寸物理模型。这种可扩展的房间声学模型（尖叫）将在许多应用中带来好处，从消费电子和通信，到电脑游戏，沉浸式媒体和建筑声学。该模型将能够实时适应，使最终用户能够获得可用计算资源允许的最佳听觉体验。一旦更强大的机器出现，音频软件开发者将不需要更新他们的开发链，从而降低成本。电子设备，如免提设备、智能扬声器和扩声系统，将能够建立一个更灵活的室内声学内部表示，使它们能够减少不必要的回声，消除声学反馈，和/或改善重放声音的音调平衡。该项目的主要假设是，物理模型和基于所谓延迟网络的感知模型之间存在联系，这种联系可以用来开发广受欢迎的统一和可扩展模型。这项研究将在萨里大学进行，并得到Sonos（音频消费电子产品）、Electronic Arts（电脑游戏）、audio Software Development Limited（电脑游戏音频咨询）和Adrian James Acoustics（声学咨询）的工业支持。

We spend the majority of our lives indoors. Within enclosed spaces, sound is reflected numerous times, leading to reverberation. We are accustomed to perceiving reverberation-we unconsciously use it to navigate the space, and, when absent, we notice. Similarly, our electronic devices, such as laptops, TVs or smart home devices, are exposed to reverberation and need to take into account its presence. Being able to predict, synthesise, and control reverberation is therefore important. This is done using room acoustic models. Existing room acoustic models suffer from two main limitations. First, they were originally developed from very different starting points and for very different purposes, which has led to a highly fragmented research field where advancements in one area do not translate to advancements in other areas, slowing down research. Second, each model has a specific accuracy and a specific computational complexity, with some very accurate models taking several days to run (physical models), while others run in real-time but with low accuracy and only aim to create a pleasing reverberant sound (perceptual models). Thus, there is no single model that allows to scale continuously from one extreme to the other. This project will overcome both limitations by defining a novel, unifying room acoustic model that combines appealing properties of all main types of models and that can scale on demand from a lightweight perceptual model to a full-scale physical model. Such a SCalable Room Acoustic Model (SCReAM) will bring benefits in many applications, ranging from consumer electronics and communications, to computer games, immersive media, and architectural acoustics. The model will be able to adapt in real time, enabling end-users to get the best possible auditory experience allowed by the available computing resources. Audio software developers will not need to update their development chains once more powerful machines become available, thus reducing costs. Electronic equipment, such as hands-free devices, smart loudspeakers, and sound reinforcement systems, will be able to build a more flexible internal representation of room acoustics, allowing them to reduce unwanted echoes, to remove acoustic feedback, and/or to improve the tonal balance of reproduced sound.The main hypothesis of the project is that a connection exists between physical models and perceptual models based on so-called delay networks, and that this connection can be leveraged to develop the sought-after unifying and scalable model.The research will be conducted at the University of Surrey with industrial support by Sonos (audio consumer electronics), Electronic Arts (computer games), Audio Software Development Limited (computer games audio consultancy), and Adrian James Acoustics (acoustics consultancy).