{"title":"一种有效的时变响度模型","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":"{\"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}","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}
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.