Tutorial 3: Amplitude Clipping Effects

Tutorial 3: Amplitude Clipping Effects

In this section, I implemented a function to model clipping effect. I modeled two types of clipping functions. Distortion function simply multiplies the input signal by the specified amplification factor and saturates all the samples above a certain threshold and its transfer function has a sharp edge at the threshold.












Overdrive function uses a softclipping approach where the output amplitude approaches an asymtototic value as input amplitude increases.











Source Code and sample Audio: tutorial3

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Dynamic Range Compression and Noise

This post accompanies our presentation “Dynamic Range Compression of Sound Mixtures” at the 2020 Acoustical Society of America meeting. Complete details are available in the paper preprint “Modeling the effects of dynamic range compression on signals in noise.”

Nearly every modern hearing aid uses an algorithm called dynamic range compression (DRC), which automatically adjusts the amplification of the hearing aid to make quiet sounds louder and loud sounds quieter. Although compression is one of the most important features of hearing aids, it might also be one of the reasons that they work so poorly in noisy environments. Hearing researchers have long known that when DRC is applied to multiple sounds at once, it can cause distortion and make background noise worse. Our research team is applying signal processing theory to understand why compression works poorly in noise and exploring new strategies for controlling loudness in noisy environments.

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