{"title":"An efficient time-varying loudness model","authors":"D. Ward, C. Athwal, M. Köküer","doi":"10.1109/WASPAA.2013.6701884","DOIUrl":null,"url":null,"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.","PeriodicalId":341888,"journal":{"name":"2013 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 IEEE Workshop on Applications of Signal Processing to Audio and Acoustics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/WASPAA.2013.6701884","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
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.