反断言,反提高了词识别:反和横向抑制如何在噪音上加敏信号
James S Magnuson1, Anne Marie Crinnion2, Sahil Luthra3
1University of Connecticut. Storrs, CT, USA; BCBL. Basque Center on Cognition Brain and Language, Donostia-San Sebastián, Spain; Ikerbasque. Basque Foundation for Science, Bilbao, Spain.
Cognition
|November 9, 2023
概括
上下反通过提高信号来增强口语识别,这与最近的说法相反. 有反和横向抑制的交互模型为认知过程提供了更节的解释.
科学领域:
- 认知科学 认知科学
- 心理语言学 心理语言学
- 计算神经科学是一种神经科学.
背景情况:
- 讨论了上下反在口语识别中的作用.
- 存在相互竞争的计算模型,关于反影响的讨论正在进行中.
研究的目的:
- 为了纠正最近对口语反在口语识别中的不准确性.
- 解释交互式激活模型如何利用反和横向抑制来提高在噪音条件下的识别精度.
主要方法:
- 检查和纠正关于反在杂环境中的作用的计算模拟.
- 审查行为和神经证据,支持词识别中的反机制.
主要成果:
- 反,当与横向抑制相结合时,可以选择性地增强词汇一致的模式,提高信号清晰度.
- 之前声称在噪音下反是无效的说法被重新评估和纠正.
结论:
- 有反的交互式激活模型为口语识别提供了一个节的解释.
- 行为和神经数据越来越多地支持反包含模型,而不是自主架构.
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