We study the behavior of hybrid random waveform models for audio signals, involving sparse random series of waveforms, with random coefficients. Similar approaches have been considered in the recent years. However, these do generally not rely on explicit models, and are of more “algorithmical” nature. The models we propose allow us to analyze mathematical properties of such signals and corresponding estimators, and derive estimation algorithms, which do not rely on complex optimization techniques.