论文标题
建模动态范围压缩对噪声中信号的影响
Modeling the effects of dynamic range compression on signals in noise
论文作者
论文摘要
助听器使用动态范围压缩（DRC），一种自动增益控制的形式，使安静的声音更大声，声音更安静。压缩可以改善听力舒适性，但也会在嘈杂的环境中引起失真。据广泛报道，刚果民主共和国的噪声表现较差，但是对这些失真效应的数学分析很少。这项工作介绍了一个数学模型，以研究噪声中DRC的行为。使用有关信号信封的统计假设，我们定义了一个有效的压缩函数，该函数模拟了在另一个信号的情况下应用于一个信号的压缩函数。该框架用于证明先前已经通过实验观察到的DRC的结果：当将DRC应用于信号的混合物中时，不相关的信号信封将变得负相关；在混合物中应用于每个声音的有效压缩比单独信号的压缩要弱。在某些条件下，这种压缩可以降低长期信噪比。这些理论结果由使用记录的语音信号的软件实验支持。
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.
