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从分类响度标度数据中推导响度增长函数。

Deriving loudness growth functions from categorical loudness scaling data.

作者信息

Wróblewski Marcin, Rasetshwane Daniel M, Neely Stephen T, Jesteadt Walt

机构信息

Boys Town National Research Hospital, Omaha, Nebraska 68131, USA.

出版信息

J Acoust Soc Am. 2017 Dec;142(6):3660. doi: 10.1121/1.5017618.

Abstract

The goal of this study was to reconcile the differences between measures of loudness obtained with continuous, unbounded scaling procedures, such as magnitude estimation and production, and those obtained using a limited number of discrete categories, such as categorical loudness scaling (CLS). The former procedures yield data with ratio properties, but some listeners find it difficult to generate numbers proportional to loudness and the numbers cannot be compared across listeners to explore individual differences. CLS, where listeners rate loudness on a verbal scale, is an easier task, but the numerical values or categorical units (CUs) assigned to the points on the scale are not proportional to loudness. Sufficient CLS data are now available to assign values in sones, a scale proportional to loudness, to the loudness categories. As a demonstration of this approach, data from Heeren, Hohmann, Appell, and Verhey [J. Acoust. Soc. Am. 133, EL314-EL319 (2013)] were used to develop a CU metric, whose values were then substituted for the original CU values in reanalysis of a large set of CLS data obtained by Rasetshwane, Trevino, Gombert, Liebig-Trehearn, Kopun, Jesteadt, Neely, and Gorga [J. Acoust. Soc. Am. 137, 1899-1913 (2015)]. The resulting data are well fitted by power functions and are in general agreement with previously published results obtained with magnitude estimation, magnitude production, and cross modality matching.

摘要

本研究的目的是调和通过连续、无界标度程序(如量级估计和量级产生)获得的响度测量值与使用有限数量离散类别(如分类响度标度,CLS)获得的响度测量值之间的差异。前一种程序产生具有比例性质的数据,但一些听众发现很难生成与响度成比例的数字,并且这些数字无法在听众之间进行比较以探索个体差异。在CLS中,听众根据言语量表对响度进行评分,这是一项较容易的任务,但分配给量表上各点的数值或分类单位(CUs)与响度不成比例。现在有足够的CLS数据可用于将宋(sone,一种与响度成比例的量表)中的值分配给响度类别。作为这种方法的一个示例,使用了Heeren、Hohmann、Appell和Verhey [《美国声学学会杂志》133, EL314 - EL319 (2013)]的数据来开发一个CU度量,然后在对Rasetshwane、Trevino、Gombert、Liebig - Trehearn、Kopun、Jesteadt、Neely和Gorga [《美国声学学会杂志》137, 1899 - 1913 (2015)]获得的一大组CLS数据进行重新分析时,用该度量的值替代原始的CU值。所得数据通过幂函数得到了很好的拟合,并且总体上与先前发表的通过量级估计、量级产生和交叉模态匹配获得的结果一致。

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