噪声中动态范围压缩对信号影响的建模
Modeling the effects of dynamic range compression on signals in noise
摘要：
助听器使用动态范围压缩（DRC），一种自动增益控制的形式，使安静的声音更响亮，响亮的声音更安静。压缩可以提高听觉舒适度，但在嘈杂的环境中也会导致失真。它已被广泛报道，DRC表现不佳的噪声，但很少有数学分析这些失真的影响。本文介绍了一种数学模型来研究噪声中的DRC行为。使用有关信号包络的统计假设，我们定义了一个有效的压缩函数，该函数对存在另一个信号时应用于一个信号的压缩进行建模。这个框架是用来证明有关DRC的结果，以前已经观察到的实验：当DRC被应用到一个混合信号，不相关的信号包络成为负相关的;有效的压缩应用到每个声音的混合物是弱于它本来是单独的信号;和压缩可以降低长期的信噪比在某些条件下。这些理论结果支持使用记录的语音信号的软件实验。
英文摘要：
Hearing aids use dynamic range compression (DRC), a form of automatic gain control, to make quiet sounds louder and loud sounds quieter. Compression can improve listening comfort, but it can also cause distortion in noisy environments. It has been widely reported that DRC performs poorly in noise, but there has been little mathematical analysis of these distortion effects. This work introduces a mathematical model to study the behavior of DRC in noise. Using statistical assumptions about the signal envelopes, we define an effective compression function that models the compression applied to one signal in the presence of another. This framework is used to prove results about DRC that have been previously observed experimentally: that when DRC is applied to a mixture of signals, uncorrelated signal envelopes become negatively correlated; that the effective compression applied to each sound in a mixture is weaker than it would have been for the signal alone; and that compression can reduce the long-term signal-to-noise ratio in certain conditions. These theoretical results are supported by software experiments using recorded speech signals.
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