Soundfield Imaging in the Ray Space

D. Markovic, F. Antonacci, A. Sarti, S. Tubaro
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引用次数: 33

Abstract

In this work we propose a general approach to acoustic scene analysis based on a novel data structure (ray-space image) that encodes the directional plenacoustic function over a line segment (Observation Window, OW). We define and describe a system for acquiring a ray-space image using a microphone array and refer to it as ray-space (or “soundfield”) camera. The method consists of acquiring the pseudo-spectra corresponding to a grid of sampling points over the OW, and remapping them onto the ray space, which parameterizes acoustic paths crossing the OW. The resulting ray-space image displays the information gathered by the sensors in such a way that the elements of the acoustic scene (sources and reflectors) will be easy to discern, recognize and extract. The key advantage of this method is that ray-space images, irrespective of the application, are generated by a common (and highly parallelizable) processing layer, and can be processed using methods coming from the extensive literature of pattern analysis. After defining the ideal ray-space image in terms of the directional plenacoustic function, we show how to acquire it using a microphone array. We also discuss resolution and aliasing issues and show two simple examples of applications of ray-space imaging.
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射线空间中的声场成像
在这项工作中,我们提出了一种基于一种新的数据结构(光线空间图像)的声学场景分析的通用方法,该数据结构对线段上的定向全声函数进行编码(观察窗口,OW)。我们定义并描述了一个使用麦克风阵列获取射线空间图像的系统,并将其称为射线空间(或“声场”)相机。该方法包括获取采样点网格对应的伪光谱,并将其重新映射到射线空间中,从而参数化穿过OW的声路径。由此产生的射线空间图像显示由传感器收集的信息,使声学场景的元素(源和反射器)易于辨别、识别和提取。该方法的主要优点是光线空间图像,无论应用是什么,都是由一个共同的(高度并行化的)处理层生成的,并且可以使用来自大量模式分析文献的方法进行处理。在根据定向全声函数定义理想的射线空间图像后,我们展示了如何使用麦克风阵列获取它。我们还讨论了分辨率和混叠问题,并展示了射线空间成像应用的两个简单例子。
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来源期刊
IEEE Transactions on Audio Speech and Language Processing
IEEE Transactions on Audio Speech and Language Processing 工程技术-工程:电子与电气
自引率
0.00%
发文量
0
审稿时长
24.0 months
期刊介绍: The IEEE Transactions on Audio, Speech and Language Processing covers the sciences, technologies and applications relating to the analysis, coding, enhancement, recognition and synthesis of audio, music, speech and language. In particular, audio processing also covers auditory modeling, acoustic modeling and source separation. Speech processing also covers speech production and perception, adaptation, lexical modeling and speaker recognition. Language processing also covers spoken language understanding, translation, summarization, mining, general language modeling, as well as spoken dialog systems.
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