In today’s world, machine learning and neural networks have taken a firm place in the everyday life of the average person. Moreover, deep learning networks are now an essential and integral tool in every scientific discipline for solving multidimensional and diverse problems. Inevitably, therefore, the field of room acoustics has also incorporated machine learning into its problem-solving techniques for all kinds of problems. In this thesis, we explore the use of deep learning networks to estimate acoustic parameters of a space, and provide a comparative analysis between the architectures used and similar publications.
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View Code? Open in Web Editor NEWThis repo contains the source code for my Electrical and Computer Engineering Diploma Thesis at Aristotle University of Thessaloniki.