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信息掩蔽的非单调性

Nonmonotonicity of informational masking.

作者信息

Oh E L, Lutfi R A

机构信息

Waisman Center, University of Wisconsin, Madison 53705, USA.

出版信息

J Acoust Soc Am. 1998 Dec;104(6):3489-99. doi: 10.1121/1.423932.

Abstract

Neff and Green [Percept. Psychophys. 41, 409-415 (1987)] report that the masking of single tones by random-frequency multitone maskers varies nonmonotonically with number of masker components (peaking at 10-50 components). In this paper it is shown that such results are well predicted by a model (the component-relative-entropy model, CoRE) wherein thresholds increase linearly with the ensemble variance of masker spectra smoothed by peripheral auditory filters [R. A. Lutfi, J. Acoust. Soc. Am. 94, 748-758 (1993)]. Three experiments were conducted. In the first, the nonmonotonic relation was replicated for 9 of 11 listeners in conditions similar to those of Neff and Green. In the second, the frequencies of masker components were fixed and the levels of components were varied randomly across presentations to simulate Gaussian noise. In this case, the nonmonotonicity and the total amount of masking for these listeners were shown to be significantly reduced. In the third experiment, masked thresholds for the signal were found to vary monotonically with the frequency spacing of masker components for a fixed number of masker components. Large individual differences among listeners were obtained in some experimental conditions. Individual as well as mean thresholds were well predicted by the CoRE model with an appropriate selection of the values of the two free parameters of the model for each listener.

摘要

内夫和格林[《知觉与心理物理学》41卷,409 - 415页(1987年)]报告称,随机频率多音掩蔽器对单音的掩蔽效应随掩蔽器成分数量呈非单调变化(在10 - 50个成分时达到峰值)。本文表明,此类结果能被一个模型(成分相对熵模型,CORE)很好地预测,在该模型中,阈值随经外周听觉滤波器平滑后的掩蔽器频谱的总体方差呈线性增加[R. A. 卢菲,《美国声学学会杂志》94卷,748 - 758页(1993年)]。进行了三项实验。在第一项实验中,11名听众中有9名在与内夫和格林相似的条件下重现了这种非单调关系。在第二项实验中,掩蔽器成分的频率固定,各成分的电平在每次呈现时随机变化以模拟高斯噪声。在这种情况下,这些听众的非单调性和掩蔽总量显著降低。在第三项实验中,对于固定数量的掩蔽器成分,发现信号的掩蔽阈值随掩蔽器成分的频率间距呈单调变化。在某些实验条件下,听众之间存在较大的个体差异。通过为每个听众适当选择模型的两个自由参数的值,CORE模型能很好地预测个体阈值以及平均阈值。

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