Spatial Audio Quality Perception (Part 2): A Linear Regression Model
Author(s) -
Robert Conetta,
et al.
Publication year - 2015
Publication title -
journal of the audio engineering society
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.234
H-Index - 60
ISSN - 1549-4950
DOI - 10.17743/jaes.2014.0047
Subject(s) - active listening , computer science , sound quality , mean squared error , quality (philosophy) , range (aeronautics) , principal component analysis , speech recognition , statistics , artificial intelligence , mathematics , engineering , philosophy , communication , epistemology , sociology , aerospace engineering
Previously-obtained data, quantifying the degree of quality degradation resulting from a range of spatial audio processes (SAPs), can be used to build a regression model of perceived spatial audio quality in terms of previously developed spatially and timbrally relevant metrics. A generalizable model thus built, employing just five metrics and two principal components, performs well in its prediction of the quality of a range of program types degraded by a multitude of SAPs commonly encountered in consumer audio reproduction, auditioned at both central and off-center listening positions. Such a model can provide a correlation to listening test data of r = 0.89, with a root mean square error (RMSE) of 11%, making its performance comparable to that of previous audio quality models and making it a suitable core for an artificial-listener-based spatial audio quality evaluation system.
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