A master thesis from Aalborg University
Parametric Tuning of Extended Reverberation Algorithm Using Neural Networks
Author(s)
Term
4. Term
Education
Publication year
2022
Submitted on
2022-05-25
Pages
66 pages
Abstract
This thesis sets out to implement an extended feedback delay network with a comprehensive set of parameters that can be estimated by a proposed neural network. The goal of the neural network is to use audio differentiation to tune the parameters of the feedback delay network, to allow it to emulate other reverberators. The feedback delay network is implemented as a VST3 audio plugin and embedded in the neural network via a proposed audio processing model. Qualitative evaluation is done on the performance of the plugin and the neural network, and a perceptual listening test is done to evaluate the subjective quality of the reverberated signals created by the estimated reverberation parameters.
Keywords
Documents
Colophon: This page is part of the AAU Student Projects portal, which is run by Aalborg University. Here, you can find and download publicly available bachelor's theses and master's projects from across the university dating from 2008 onwards. Student projects from before 2008 are available in printed form at Aalborg University Library.
If you have any questions about AAU Student Projects or the research registration, dissemination and analysis at Aalborg University, please feel free to contact the VBN team. You can also find more information in the AAU Student Projects FAQs.