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A Detection-Theoretic Analysis of Auditory Streaming and Its Relation to Auditory Masking

机译:听觉流的检测理论分析及其与听觉掩蔽的关系

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Research on hearing has long been challenged with understanding our exceptional ability to hear out individual sounds in a mixture (the so-called cocktail party problem). Two general approaches to the problem have been taken using sequences of tones as stimuli. The first has focused on our tendency to hear sequences, sufficiently separated in frequency, split into separate cohesive streams (auditory streaming). The second has focused on our ability to detect a change in one sequence, ignoring all others (auditory masking). The two phenomena are clearly related, but that relation has never been evaluated analytically. This article offers a detection-theoretic analysis of the relation between multitone streaming and masking that underscores the expected similarities and differences between these phenomena and the predicted outcome of experiments in each case. The key to establishing this relation is the function linking performance to the information divergence of the tone sequences, DKL (a measure of the statistical separation of their parameters). A strong prediction is that streaming and masking of tones will be a common function of DKL provided that the statistical properties of sequences are symmetric. Results of experiments are reported supporting this prediction.
机译:长期以来,关于听力的研究一直面临着挑战,即理解我们出色的能力来聆听混合中的单个声音(所谓的鸡尾酒会问题)。使用音调序列作为刺激,已经采取了两种解决该问题的一般方法。第一个重点是我们倾向于听取频率上充分分离的序列,将其分成独立的内聚流(听觉流)。第二个重点是我们检测一个序列中的变化而忽略所有其他变化(听觉掩蔽)的能力。这两种现象显然是相关的,但从未对这种关系进行过分析评估。本文提供了多音流和掩蔽之间关系的检测理论分析,强调了这些现象与每种情况下实验的预期结果之间的预期相似性和差异。建立这种关系的关键是将性能与音调序列的信息差异DKL(一种衡量其参数的统计间隔的指标)联系起来的功能。一个强有力的预测是,如果序列的统计属性是对称的,则音频的流式传输和掩盖将是DKL的常见功能。据报道实验结果支持这一预测。

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