Description
In order to categorize different types of music, humans created the classified designations known as musical genres. A musical genre can be recognized by the characteristics that its participants share. These characteristics frequently relate to the harmonic structure, rhythmic structure, and musical instruments. It is common practice to use genre hierarchies to organize the enormous online music collections. Musical genre annotation is still done by hand. Automatic musical genre classification, which can supplement or even replace the human user in this process, would greatly benefit music information retrieval systems. Throughout human history, music has been extensively researched and appreciated for its capacity to amuse and heal.The main focus is on the creation of an acoustical model based on MATLAB, which categorizes different songs into their genre based on acoustical features, which is then compared to the original classification. Furthermore, it is to look into how strongly the genres can be differentiated and if there is a change in the acoustic properties throughout history. As an optional feature it is proposed to create a similar algorithm in a machine learning model which can then answer the question if there is a performance difference.