双耳声音的自然统计
Natural statistics of binaural sounds
摘要：
双耳声音定位通常被认为是一项辨别任务，其中利用纯频率通道处的耳间时间（ITD）和水平（ILD）差异来识别声源的位置。在自然条件下，双耳电路暴露于源自多个、通常移动和重叠的源的声波的刺激。因此，双耳线索的统计取决于声学特性和环境的空间配置。为了有效地处理双耳声音，听觉系统应该适应自然遇到的线索分布。以前从未研究过自然遇到的线索的统计数据及其对听觉场景物理特性的依赖性。在这里，我们进行了双耳录音的三个听觉场景具有不同的空间特性。我们已经分析了经验线索分布从每个场景，通过拟合它们与参数概率密度函数，允许一个简单的比较不同的场景。通过独立分量分析（ICA）和学习基函数的性质，分析了双耳波形的高阶统计量。所获得的结果可以与已知的神经元机制，并建议如何双耳听力可以理解的适应自然信号统计。
英文摘要：
Binaural sound localization is usually considered a discrimination task, where interaural time (ITD) and level (ILD) disparities at pure frequency channels are utilized to identify a position of a sound source. In natural conditions binaural circuits are exposed to a stimulation by sound waves originating from multiple, often moving and overlapping sources. Therefore statistics of binaural cues depend on acoustic properties and the spatial configuration of the environment. In order to process binaural sounds efficiently, the auditory system should be adapted to naturally encountered cue distributions. Statistics of cues encountered naturally and their dependence on the physical properties of an auditory scene have not been studied before. Here, we performed binaural recordings of three auditory scenes with varying spatial properties. We have analyzed empirical cue distributions from each scene by fitting them with parametric probability density functions which allowed for an easy comparison of different scenes. Higher order statistics of binaural waveforms were analyzed by performing Independent Component Analysis (ICA) and studying properties of learned basis functions. Obtained results can be related to known neuronal mechanisms and suggest how binaural hearing can be understood in terms of adaptation to the natural signal statistics.
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