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Auditory Feature Binding and Its Hierarchical Computational Model

机译:听觉特征绑定及其层次计算模型

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摘要

When we intend to grasp a sound target, perhaps its signal is in the presence of competing signals. An effective solution is to concentrate on the target's sound features selected and extracted from the various mixed auditory features. This is so-called auditory feature binding. It plays an important role in the cognitive and neuroscience. In this paper, we will describe the conceptual frame named "auditory feature binding" and then put forward its hierarchical computational model. We think that it may be used in machine auditory perception which will over-fly from the primary audition sense to the senior audition perception and cognition. Besides, we will later combine it with visual feature binding to realize cooperation of vision-audition cross-modal perception which is emphasized in the National Science Fund of China Project "Research on Synergic Learning Algorithm of vision-audition Cross-modal Coherence".
机译:当我们打算抓住一个声音目标时,它的信号可能存在​​竞争信号。一种有效的解决方案是集中于从各种混合听觉特征中选择和提取的目标的声音特征。这就是所谓的听觉特征绑定。它在认知和神经科学中起着重要作用。在本文中,我们将描述名为“听觉特征绑定”的概念框架,然后提出其层次计算模型。我们认为,它可能会用于机器听觉感知,它将从主要的听觉感觉过渡到高级的听觉感觉和认知。此外,我们稍后将其与视觉特征绑定相结合,以实现视觉-听觉跨模态感知的合作,这在国家科学基金项目“视觉-听觉跨模态一致性的协同学习算法研究”中得到了强调。

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