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The cocktail-party problem revisited: early processing and selection of multi-talker speech

机译:重新讨论了鸡尾酒会的问题:多说话者语音的早期处理和选择

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摘要

How do we recognize what one person is saying when others are speaking at the same time? This review summarizes widespread research in psychoacoustics, auditory scene analysis, and attention, all dealing with early processing and selection of speech, which has been stimulated by this question. Important effects occurring at the peripheral and brainstem levels are mutual masking of sounds and “unmasking” resulting from binaural listening. Psychoacoustic models have been developed that can predict these effects accurately, albeit using computational approaches rather than approximations of neural processing. Grouping—the segregation and streaming of sounds—represents a subsequent processing stage that interacts closely with attention. Sounds can be easily grouped—and subsequently selected—using primitive features such as spatial location and fundamental frequency. More complex processing is required when lexical, syntactic, or semantic information is used. Whereas it is now clear that such processing can take place preattentively, there also is evidence that the processing depth depends on the task-relevancy of the sound. This is consistent with the presence of a feedback loop in attentional control, triggering enhancement of to-be-selected input. Despite recent progress, there are still many unresolved issues: there is a need for integrative models that are neurophysiologically plausible, for research into grouping based on other than spatial or voice-related cues, for studies explicitly addressing endogenous and exogenous attention, for an explanation of the remarkable sluggishness of attention focused on dynamically changing sounds, and for research elucidating the distinction between binaural speech perception and sound localization.
机译:当别人同时讲话时,我们如何识别一个人在说什么?这篇综述总结了在心理声学,听觉场景分析和注意力方面的广泛研究,这些研究都与早期处理和语音选择有关,这受到了这个问题的刺激。在周围和脑干水平发生的重要影响是声音的相互掩盖和双耳聆听导致的“掩盖”。尽管使用了计算方法而不是神经处理的近似方法,但已经开发出可以准确预测这些影响的心理声学模型。分组-声音的分离和流化-表示随后的处理阶段,与注意力密切交互。可以使用原始特征(例如空间位置和基频)轻松地对声音进行分组,然后进行选择。当使用词汇,句法或语义信息时,需要更复杂的处理。现在很明显,这种处理可以集中精力进行,但也有证据表明处理深度取决于声音的任务相关性。这与注意力控制中存在反馈回路相一致,从而触发了待选择输入的增强。尽管取得了新的进展,但仍然存在许多未解决的问题:需要一种在神经生理学上可行的整合模型,用于基于空间或语音相关线索以外的分组研究,用于明确解决内源性和外源性注意力的研究,以进行解释注意力的显着呆滞集中于动态变化的声音,以及旨在阐明双耳语音感知与声音本地化之间的区别的研究。

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