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音调序列辨别中的时间因素。

Temporal factors in the discrimination of tonal sequences.

作者信息

Sorkin R D

机构信息

Department of Psychological Sciences, Purdue University, West Lafayette, Indiana 47907.

出版信息

J Acoust Soc Am. 1987 Oct;82(4):1218-26. doi: 10.1121/1.395258.

Abstract

Human observers were asked to judge whether or not two sequences of eight or more tones had the same serial pattern of frequencies. The temporal envelopes of the sequences were manipulated by randomly varying the tone durations or intertone gaps. In the correlated condition, the temporal envelopes of the sequences were varied across trials; the two sequences within each trial had the same temporal envelope. In the uncorrelated condition, the temporal envelopes were varied both across and within trials; every sequence had a unique temporal pattern. Performance in the uncorrelated condition decreased with increased variability in the temporal envelope. Performance in the correlated condition was independent of temporal variability, but decreased with increases in the time interval between the onsets of the two sequences. This pattern of results is consistent with an extension of a model of auditory discrimination developed by Durlach and Braida [J. Acoust. Soc. Am. 46, 372-383 (1969)], in which two processing modes are postulated: a trace mode and a context mode. When the tonal sequences had unique temporal patterns, context mode processing was dominant; when the sequences had identical temporal patterns, trace mode processing was preferred. The effect of variables such as the number of tones, the tone duration, the time gap between tones, and the time interval between sequences was consistent with the predictions of the discrimination model.

摘要

研究人员要求人类观察者判断两个包含八个或更多音调的序列是否具有相同的频率序列模式。通过随机改变音调持续时间或音调间隔来操纵序列的时间包络。在相关条件下,序列的时间包络在不同试验中变化;每次试验中的两个序列具有相同的时间包络。在不相关条件下,时间包络在试验之间和试验内均发生变化;每个序列都有独特的时间模式。在不相关条件下,随着时间包络变异性的增加,表现会下降。在相关条件下,表现与时间变异性无关,但随着两个序列起始之间的时间间隔增加而下降。这一结果模式与Durlach和Braida [《美国声学学会杂志》46, 372 - 383 (1969)] 提出的听觉辨别模型的扩展一致,该模型假设了两种处理模式:痕迹模式和上下文模式。当音调序列具有独特的时间模式时,上下文模式处理占主导;当序列具有相同的时间模式时,痕迹模式处理更受青睐。音调数量、音调持续时间、音调之间的时间间隔以及序列之间的时间间隔等变量的影响与辨别模型的预测一致。

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