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Proceedings Paper

Importance of perceptive adaptation of sound features in audio content processing
Author(s): Silvia Pfeiffer
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Paper Abstract

The importance of perceptive modeling for calculation of sound features is well known. Use of simple perception-based adaptations of physically measured stimuli, such as the dB- scale or loudness, is a minimal requirement. Exactly how much value can be gained by more complex perceptive modeling, has not been investigated in detail. The paper examines this question for loudness measures, using well- known psychoacoustic knowledge for their calculation. Profiles of these measures are calculated on audio data of movie material, deliberately using 'natural' sound, instead of reverting to artificial sounds in the laboratory. Ultimately, the quality of a sound feature can only be judged by comparison to human estimates. Therefore, test people were asked to express their perception of loudness by continuous classification into five classes (called pp, p, mf, f, and ff). The results were used to evaluate two loudness measures: the sound pressure level, and an integral loudness measure, developed in the discussed research. The correlation of the human loudness estimates to the integral loudness measure, is about 10 percent higher than to the sound pressure level. In addition, the integral loudness results in a significantly better approximation of the curve of human loudness estimates.

Paper Details

Date Published: 17 December 1998
PDF: 10 pages
Proc. SPIE 3656, Storage and Retrieval for Image and Video Databases VII, (17 December 1998); doi: 10.1117/12.333852
Show Author Affiliations
Silvia Pfeiffer, Univ. of Mannheim (Australia)


Published in SPIE Proceedings Vol. 3656:
Storage and Retrieval for Image and Video Databases VII
Minerva M. Yeung; Boon-Lock Yeo; Charles A. Bouman, Editor(s)

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