Spectral weights in profile listening.
Spectral weights in profile listening.
复制标题
剖面聆听中的频谱权重。
DOI：
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发表时间：
1990
影响因子：
2.4
通讯作者：
D. Green
中科院分区：
文献类型：
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作者：
B. Berg;D. Green
Berg 建议的 COSS 分析 [B. G.伯格，J.阿库斯特。苏克。是。 86, 1743-1746 (1989)]应用于配置文件监听任务。收听者的任务是检测 n 分量频谱的中间分量的电平增量。每次演示时，组件的总体电平都是从 20 dB 范围内随机选择的；因此，检测任务本质上是检测光谱形状的变化。为了实施 COSS 分析，在复合体的每个组成部分中添加了一个小的水平扰动。 COSS 函数是根据这些扰动生成的，并且估计听者分配给每个分量的频谱权重。报告了 n = 3、5 和 11 个分量的数据以及标准偏差为 0.5、1 和 2 dB 的扰动。估计的权重与最佳检测器导出的权重类似；即，将信号分量的电平与非信号分量的平均电平进行比较。这一结果支持了概况分析涉及跨渠道比较过程的观点。权重模式还可以洞察听众之间的差异。在单独的实验中，估计了非常差的轮廓侦听器的频谱权重，并且权重的模式表明了检测性能较差的原因。
The COSS analysis suggested by Berg [B. G. Berg, J. Acoust. Soc. Am. 86, 1743-1746 (1989)] is applied to a profile listening task. The listener's task is to detect an increment in the level of the middle component of an n-component spectrum. The overall level of the components is randomly selected from a 20-dB range on each presentation; thus the detection task is essentially one of detecting a change in spectral shape. To implement the COSS analysis, a small perturbation in level is added to each component of the complex. COSS functions are generated from these perturbations, and the spectral weight that the listener assigns to each component is estimated. Data are reported for n = 3, 5, and 11 components and for perturbations with standard deviations of 0.5, 1, and 2 dB. The estimated weights are similar to those derived for an optimum detector; namely, the level at the signal component is compared with the average level of the nonsignal components. This result supports the view that profile analysis involves an across-channel comparison process. The pattern of weights also provides insight into differences among listeners. In a separate experiment, the spectral weights of a very poor profile listener are estimated, and the pattern of the weights suggests reasons for the inferior detection performance.