Models of room acoustical perception

将开发感知模型，其预测对房间声学属性的感知，例如宽敞度、表观源宽度、收听者注意力、混响、温暖度、亮度、清晰度、透明度和响度。而大多数现有的方法是基于信号统计的，耳间互相关（IACC），所提出的工作将基于一个听觉前端，创建一个信号表示，是'内部'提供给听众。使用这样的内部表示允许在感知相关的信号属性和听不见的属性之间进行区分。这应该能够更准确地预测房间声学的感知。室内声学模拟的变化将用于创建不同程度的室内声学变化，这些变化可以由人类听众进行评估，并根据模型预测进行测试，以适应和改进感知模型。这里的目标都将是准确地预测辨别力的房间声学模拟是彼此接近（作为测试模型中内部表示的基本有效性的手段）并预测感知的房间声学属性，例如混响，通过听音测试和听觉实验，研究了头部朝向在感知房间声学感知属性中的作用。模型开发。

Perceptual models will be developed that predict the perception of room acoustical attributes such as spaciousness, apparent source width, listener envelopment, reverberance, warmth, brilliance, clarity, transparency, and loudness. Whereas most existing approaches are based on signal statistics such as e.g., InterAural Cross Correlation (lACC), the proposed work will be based on an auditory front-end that creates a signal representation that is 'internally' available to the listener. Using such an internal representation allows to make a distinction between signal properties that are perceptually relevant and properties that are inaudible. This should enable a more accurate prediction of the perception of room acoustics. Variations in room acoustical simulations will be used to create room acoustical variations of different degrees that can be evaluated by human listeners and tested against model predictions to adapt and improve the perceptual models. Here the aim will both be to accurately predict discriminability of room acoustical simulations that are close to one another (as a means to test the basic validity of the internal representations in the model) and to predict perceived room acoustical attributes such as envelopment, reverberance, etc. The role of head orientation in the perception of room acoustical perceptual attributes will be investigated by listening tests and in the perceptual models developed.