Objectives

The study of singing style in popular music is an emerging branch in musicology, while effects related to singing style have become a central part of the majority of popular music productions making use of the few effect plugins that are available today. ARS aims to establish a mutually beneficial collaboration between musicologists working on singing performance and specialists in signal processing, with the following objectives: 1) to exploit advances in voice signal processing and deep learning for musicological research on singing style and 2) to develop new algorithms for high quality expressive singing voice transformation that diversify and enrich the palette of artistic expressions in popular music. Musicologists will contribute to the development of singing effects with their expertise about musically and artistically relevant singing style features, while signal-processing specialist will establish robust analysis algorithms for musicologists to study singing style in real music performances, and innovative singing voice transformation algorithms that allow modification of singing style in music productions.