Public defence in Acoustics and Audio Signal Processing, M.Sc. Karolina Prawda
M.Sc. Karolina Prawda will defend the thesis "Room Reverberation Prediction and Synthesis" on 21 October 2022 at 12 (EET) in Aalto University School of Electrical Engineering, Department of Signal Processing and Acoustics, in lecture hall Jeti, Otakaari 5, Espoo, and online in Zoom.
Opponent: Prof. Peter Svensson, NTNU, Norway
Custos: Prof. Vesa Välimäki, Aalto University School of Electrical Engineering, Department of Signal Processing and Acoustics
The public defence will be organized via remote technology. Follow defence: https://aalto.zoom.us/j/5274681647
Zoom Quick Guide: https://www.aalto.fi/en/services/zoom-quick-guide
Thesis available for public display at: https://aaltodoc.aalto.fi/doc_public/eonly/riiputus/
Doctoral theses in the School of Electrical Engineering: https://aaltodoc.aalto.fi/handle/123456789/53
Public defence announcement:
The research presented in this dissertation offers improvements and insights into the methods of reverberation prediction, measurement, and synthesis. These are crucial for both designs of spaces such as concert halls and classrooms, as well as virtual spaces, computer games and audio software.
The results of the dissertation allow for reliable estimation of parameters related to sound energy decay and offer an improvement in the field of artificial reverberation.
The dissertation discusses the properties of sound decay in enclosed spaces, also known as reverberation, which is one of the most prominent features of sound propagation in rooms. Reverberation time, the main parameter associated with sound energy decay, is a well-known quantity, widely used in architectural design of e.g. concert halls and classrooms.
Reverberation prediction methods have been known since the early 1900’s, and their accuracy and applicability has been constantly refined since then. To further advance those methods, a large dataset of reverberation samples was recorded in the Aalto University variable acoustics lab. Using this dataset, the main sources of prediction error were identified, and their impact could then be lowered. Through this a procedure to increase prediction accuracy was proposed and validated.
Reverberation measurements are discussed with a focus on the exponential swept-sine technique. The factors negatively impacting measurements, such as stationary and non-stationary noise and time variance are analyzed, and a robust method – the rule of two -- of detecting clean sweeps in a set with noisy measurements, is presented.
Artificial reverberation algorithms, aimed at synthesizing sound energy decay digitally, are studied in the dissertation. The two main techniques are the feedback delay network and velvet noise-based algorithms. These are explored from a perspective of accurately reproducing target reverberation, as well as analyzing aspects of artificial reverberation, that affect the perceptual qualities of synthesized sound.
Contact information of doctoral candidate