DocumentCode
667538
Title
An efficient time-varying loudness model
Author
Ward, D. ; Athwal, Cham ; Kokuer, Munevver
Author_Institution
Sch. of Digital Media Technol., Birmingham City Univ. Birmingham, Birmingham, UK
fYear
2013
fDate
20-23 Oct. 2013
Firstpage
1
Lastpage
4
Abstract
In this paper, we present an efficient loudness model applicable to time-varying sounds. We use the model of Glasberg and Moore (J. Audio Eng. Soc., 2002) as the basis for our developments, proposing a number of optimization techniques to reduce the computational complexity at each stage of the model. Efficient alternatives to computing the multi-resolution DFT, excitation pattern and pre-cochlea filter are presented. Absolute threshold and equal loudness contour predictions are computed and compared against both steady-state and time-varying loudness models to evaluate the combined accuracy of these techniques in the frequency domain. Finally, computational costs and loudness errors are quantified for a range of time-varying stimuli, demonstrating that the optimized model can execute approximately 50 times faster within tolerable error bounds.
Keywords
acoustic signal processing; computational complexity; discrete Fourier transforms; filtering theory; frequency-domain analysis; optimisation; absolute threshold; computational complexity reduction; computational costs; equal loudness contour predictions; excitation pattern; loudness errors; multiresolution DFT; optimization techniques; pre-cochlea filter; steady-state loudness models; time-varying loudness model; time-varying sounds; time-varying stimuli; tolerable error bounds; Acoustics; Computational modeling; Discrete Fourier transforms; Ear; Frequency-domain analysis; Predictive models; Psychoacoustic models; loudness; perceptual models; psychoacoustics;
fLanguage
English
Publisher
ieee
Conference_Titel
Applications of Signal Processing to Audio and Acoustics (WASPAA), 2013 IEEE Workshop on
Conference_Location
New Paltz, NY
ISSN
1931-1168
Type
conf
DOI
10.1109/WASPAA.2013.6701884
Filename
6701884
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