论文标题
基于真实声源的本地化和一阶反射的室内几何盲目推理
Room geometry blind inference based on the localization of real sound source and first order reflections
论文作者
论文摘要
传统的房间几何学几何推理技术具有声学信号是根据环境的先验知识进行的，例如房间脉冲响应（RIR）或声源位置，这将限制其在未知场景下的应用。为了解决这个问题，我们通过使用直接信号和一阶反射之间的几何关系提出了本文中的房间几何重建方法。除了紧凑的麦克风阵列本身的信息外，此方法不需要对环境参数的任何预先认识。此外，基于学习的DNN模型旨在提高直接源和一阶反射的本地化结果的准确性和完整性。首先，使用所提出的DCNN和TD-CNN模型估算到达和反射信号的到达的方向（DOA）和到达的时间差（TDOA）信息，这些模型比传统方法具有更高的灵敏度和准确性。然后，使用建议的DNN模型通过集成DOA，TDOA和阵列高度来推断声源的位置。之后，基于几何关系得出图像源和相应边界的位置。模拟和实际测量结果的实验结果验证了与不同的回响环境下的常规方法相比，所提出的技术的有效性和准确性。
The conventional room geometry blind inference techniques with acoustic signals are conducted based on the prior knowledge of the environment, such as the room impulse response (RIR) or the sound source position, which will limit its application under unknown scenarios. To solve this problem, we have proposed a room geometry reconstruction method in this paper by using the geometric relation between the direct signal and first-order reflections. In addition to the information of the compact microphone array itself, this method does not need any precognition of the environmental parameters. Besides, the learning-based DNN models are designed and used to improve the accuracy and integrity of the localization results of the direct source and first-order reflections. The direction of arrival (DOA) and time difference of arrival (TDOA) information of the direct and reflected signals are firstly estimated using the proposed DCNN and TD-CNN models, which have higher sensitivity and accuracy than the conventional methods. Then the position of the sound source is inferred by integrating the DOA, TDOA and array height using the proposed DNN model. After that, the positions of image sources and corresponding boundaries are derived based on the geometric relation. Experimental results of both simulations and real measurements verify the effectiveness and accuracy of the proposed techniques compared with the conventional methods under different reverberant environments.
