Dense Reverberation with Delay Feedback Matrices

Sebastian J Schlecht, Emanuël A P Habets

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

This paper received the [Best Paper Award](http://waspaa.com/).
Feedback delay networks (FDNs) belong to a general class of recursive filters which are widely used in artificial reverberation and decorrelation applications. One central challenge in the design of FDNs is the generation of sufficient echo density in the impulse response without compromising the computational efficiency. In a previous contribution, we have demonstrated that the echo density of an FDN grows polynomially over time, and that the growth depends on the number and lengths of the delays. In this work, we introduce so-called delay feedback matrices (DFMs) where each matrix entry is a scalar gain and a delay. While the computational complexity of DFMs is similar to a scalar-only feedback matrix, we show that the echo density grows significantly faster over time, however, at the cost of non-uniform modal decays.
Original languageEnglish
Title of host publicationIEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA)
PublisherIEEE
Pages1 - 5
DOIs
Publication statusPublished - 2019
MoE publication typeA4 Article in a conference publication
EventIEEE Workshop on Applications of Signal Processing to Audio and Acoustics - New York, United States
Duration: 20 Oct 201923 Oct 2019
Conference number: 23
https://www.waspaa.com/

Workshop

WorkshopIEEE Workshop on Applications of Signal Processing to Audio and Acoustics
Abbreviated titleWASPAA
CountryUnited States
CityNew York
Period20/10/201923/10/2019
Internet address

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