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The role of speech fidelity in the irrelevant sound effect: Insights from noise-vocoded speech backgrounds

机译:语音保真度在无关紧要的声音效果中的作用:噪声声学背景中的洞察力

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The Irrelevant Sound Effect (ISE) is the finding that background sound impairs accuracy for visually presented serial recall tasks. Among various auditory backgrounds, speech typically acts as the strongest distractor. Based on the changing-state hypothesis, speech is a disruptive background because it is more complex than other nonspeech backgrounds. In the current study, we evaluate an alternative explanation by examining whether the speech-likeness of the background (speech fidelity) contributes, beyond signal complexity, to the ISE. We did this by using noise-vocoded speech as a background. In Experiment 1, we varied the complexity of the background by manipulating the number of vocoding channels. Results indicate that the ISE increases with the number of channels, suggesting that more complex signals produce greater ISEs. In Experiment 2, we varied complexity and speech fidelity independently. At each channel level, we selectively reversed a subset of channels to design a low-fidelity signal that was equated in overall complexity. Experiment 2 results indicated that speech-like noise-vocoded speech produces a larger ISE than selectively reversed noise-vocoded speech. Finally, in Experiment 3, we evaluated the locus of the speech-fidelity effect by assessing the distraction produced by these stimuli in a missing-item task. In this task, even though noise-vocoded speech disrupted task performance relative to silence, neither its complexity nor speech fidelity contributed to this effect. Together, these findings indicate a clear role for speech fidelity of the background beyond its changing-state quality and its attention capture potential.
机译:无关的声音效果(ISE)是发现背景声音危害直观呈现串行召回任务的精度。在各种听觉背景中,言语通常充当最强的分心。基于改变状态假设,言语是一个破坏性背景,因为它比其他非晶片背景更复杂。在目前的研究中,我们通过检查背景(语音保真度)的语音符号是否有助于超越信号复杂度来评估替代解释。我们通过使用噪声声音语音作为背景来完成此操作。在实验1中,我们通过操纵声码信道的数量来改变背景的复杂性。结果表明,ISE随着通道的数量增加,表明更复杂的信号产生更大的ISE。在实验2中,我们独立变化了复杂性和语音保真度。在每个频道级别,我们选择性地反转了一个通道的子集,以设计一个等同于整体复杂性的低保真信号。实验2结果表明,语音噪声声语音的语音产生比选择性地逆转噪声声学语音更大的ISE。最后,在实验3中,我们通过评估这些刺激在缺失的项目任务中产生的分担来评估语音保真效果的基因座。在这项任务中,即使噪声声音语音相对于沉默中断了任务性能,它们都没有其复杂性和语音保真度贡献这一效果。这些发现在一起,表明背景的语音保真在超出其变化状态和注意力捕获潜力的情况下的语音保真度。

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