Transient-to-noise ratio restoration of coded applause-like signals

Coding of signals with high amount of dense transient events, like applause, rain drops, etc., is usually a difficult task for perceptual audio coders. Especially at low bit rates, coding (and the associated coding noise) leads to smeared transients and a perceived increase in noise-like signal character. We propose a post-processing technique for coded/decoded applause-like signals which is based on a signal decomposition into foreground (transient) clap events and a more noise-like background part. The proposed method aims at restoring the transient-to-noise ratio of the decoded signal using a static frequency-dependent restoration profile. The method is shown to provide a significant improvement in subjective audio quality (MUSHRA score) when applied to signals originating from a state-of-the-art audio codec in different configurations.