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Towards an audio attribute framework for understanding the perception of reverberant spaces through elicitation and clustering methods based on participant expectation

Child, Luke; Ford, Natanya

Authors

Luke Child



Abstract

When used in perceptual audio evaluation, elicitation methods produce a wide variety of raw and unorganized text data. Although at first ambiguous, elicited data can be organized into themes and attributes that are intrinsic to the listener experience. This paper seeks to compare the trends found in descriptions of reverberant locations from memory, isolating key attributes and phrases present in descriptions. These attributes are then cleaned, validated, and clustered to form a series of key parent attributes that encompass the descriptions of the original attributes. Methods for the optimization of each stage are discussed, alongside applications for understanding and utilizing the attributes in future implementations of digital reverberation.

Citation

Child, L., & Ford, N. (2021). Towards an audio attribute framework for understanding the perception of reverberant spaces through elicitation and clustering methods based on participant expectation. In Audio Engineering Society Convention 150

Conference Name Audio Engineering Society Convention 150
Conference Location Online
Start Date May 25, 2021
End Date May 28, 2021
Acceptance Date Apr 19, 2021
Online Publication Date May 25, 2021
Publication Date 2021
Deposit Date May 28, 2021
Publisher Audio Engineering Society
Book Title Audio Engineering Society Convention 150
Public URL https://uwe-repository.worktribe.com/output/7428941
Publisher URL http://www.aes.org/e-lib/browse.cfm?elib=21060
Related Public URLs https://www.aes.org/tmpFiles/elib/20210528/21060.pdf