Supervision: Benjamin Ricaud

Project type: Semester project (bachelor) Semester project (master)


Bass music enthusiasts appreciate nothing more than the blast from their subwoofers, expressed as a sustained, powerful low-frequency pitch that induces a physical response of the body. But there are not so many people aware that this booming sound reveals a critical defect of listening rooms, are a real nightmare for sound engineers and can be potentially harmful to the hear.

More precisely, the music industry influences the preferences of the public in terms of sound quality for more than 30 years. A significant boost in the low-frequency range has occured since the 1980's, due to the rise of the disco music, but also as a results of signal compressions (eg. for FM radio broadcasting among other reasons).

This project aims at revealing the bass-boost trends in the music industry, by analyzing a set of musical excerpts. The methodology will be the following:

  • define a set of musical excerpts. The Montreux Jazz Festival archive will be used (thousands of hours of concerts over 49 years have been recorded and are available for research purpose).

  • identify / define a set of signal features that reveal the bass characteristics of the sample

  • process the signals and analyze the results

Profile: Electrical engineering, Communication Science

Prerequisites: basic signal processing (filtering, Fourier transform) and data handling

Context: Matlab or Python. Experience in data visualization or a motivation to learn it, especially interactive visualization, will be appreciated