论文标题
从环境噪声中估算二元时频面膜
Estimation of binary time-frequency masks from ambient noise
论文作者
论文摘要
我们从几个观察到过滤的白色环境噪声中研究了二元时间频面掩模的检索。在声学建模中证实了家庭智慧，我们证明了通过检查环境噪声的平均光谱图是可能的。具体而言，我们表明$ \ MATHCAL {O}的平均分位数（\ log（|ω|/\ Varepsilon））$掩盖的频谱图足以识别一个相当通用的蒙版$ω$，并自信至少$ \ \ varepsilon $，以形成附近的详细信息。作为应用程序，估计误差的预期度量由时频掩模的周长主导。估算器不需要了解噪声差异，并且只需要对过滤窗口的定性概况，但没有确切的知识。
We investigate the retrieval of a binary time-frequency mask from a few observations of filtered white ambient noise. Confirming household wisdom in acoustic modeling, we show that this is possible by inspecting the average spectrogram of ambient noise. Specifically, we show that the lower quantile of the average of $\mathcal{O}(\log(|Ω|/\varepsilon))$ masked spectrograms is enough to identify a rather general mask $Ω$ with confidence at least $\varepsilon$, up to shape details concentrated near the boundary of $Ω$. As an application, the expected measure of the estimation error is dominated by the perimeter of the time-frequency mask. The estimator requires no knowledge of the noise variance, and only a very qualitative profile of the filtering window, but no exact knowledge of it.
