Concurrent categorical scaling of sound quality measures (CCSM) – a database of psychoacoustic measures roughness, sharpness, tonality, loudness and annoyance of artificial and real sounds

To connect sound quality with other psychoacoustic measures experimentally and for model evaluation, a benchmark set of simultaneously assessed measures with a large set of signals is highly desirable. Hence, two experiments were conducted, in which roughness, sharpness, tonality, loudness and annoyance were assessed for a total of 129 artificial and real sounds by normal-hearing listeners using a categorical scale. The instrumental loudness was equalized for most of the sounds to limit the influence of loudness. With test-retest correlation of r²>0.76 for all attributes, results indicated the reliability of the method. Correlation analyses and a multilinear regression revealed that, besides loudness, sharpness contributed most to annoyance (r²=0.72), while roughness (r²=0.04) and tonality (r²=0.08) did not contribute significantly. The present data set demonstrates the applicability of a categorical scale for the concurrent assessment of psychoacoustical properties and can serve as a basis for further research that is required to accurately model psychoacoustic measures for a broad range of signals.

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Publication Details

Journal
Fraunhofer-Publica (Fraunhofer-Gesellschaft)
Published
2025-11-14
DOI
https://doi.org/10.3205/zaud000073
Primary Topic
Hearing Loss and Rehabilitation
Type
article
Field-Weighted Citation Impact
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article

Concurrent categorical scaling of sound quality measures (CCSM) – a database of psychoacoustic measures roughness, sharpness, tonality, loudness and annoyance of artificial and real sounds

Fraunhofer-Publica (Fraunhofer-Gesellschaft)
Hearing Loss and Rehabilitation
article

Concurrent categorical scaling of sound quality measures (CCSM) – a database of psychoacoustic measures roughness, sharpness, tonality, loudness and annoyance of artificial and real sounds

article en

Abstract

To connect sound quality with other psychoacoustic measures experimentally and for model evaluation, a benchmark set of simultaneously assessed measures with a large set of signals is highly desirable. Hence, two experiments were conducted, in which roughness, sharpness, tonality, loudness and annoyance were assessed for a total of 129 artificial and real sounds by normal-hearing listeners using a categorical scale. The instrumental loudness was equalized for most of the sounds to limit the influence of loudness. With test-retest correlation of r²>0.76 for all attributes, results indicated the reliability of the method. Correlation analyses and a multilinear regression revealed that, besides loudness, sharpness contributed most to annoyance (r²=0.72), while roughness (r²=0.04) and tonality (r²=0.08) did not contribute significantly. The present data set demonstrates the applicability of a categorical scale for the concurrent assessment of psychoacoustical properties and can serve as a basis for further research that is required to accurately model psychoacoustic measures for a broad range of signals.

Fraunhofer-Publica (Fraunhofer-Gesellschaft)
Carl von Ossietzky Universität Oldenburg (DE), Fraunhofer Institute for Digital Media Technology (DE), Hearing4all (DE)
Quality Education
Openalex Percentile: Top 42%
Hearing Loss and Rehabilitation
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