Background noise classification and denoising of audio signals utilizing empirical wavelet transform and deep learning

2021

Master´s thesis in Information and Communication Technology (IKT590), University of Agder, Grimstad The importance of sound and speech cannot in human life cannot be overstated. Ambient sound informs us about our surroundings and warn us of potential dangers, such as a car approaching from behind. One of the most common modes of communication is speech. However, if it is contaminated with background noise, it may result in data loss. Recent advances in artificial intelligence enable machines to recognize and classify sound patterns, as well as remove complex background noise from contaminated speech. This thesis investigates a method for improving existing background noise classification an…