贝叶斯主动声音定位:人类在多大程度上表现得像一个理想的观察者?
Glen McLachlan1, Piotr Majdak2, Jonas Reijniers1
1Department of Engineering Management, University of Antwerp, Antwerp, Belgium.
PLoS computational biology
|January 8, 2025
概括
人类的声音定位依赖于将头部运动与听觉线索相结合. 一个理想的观察者模型部分预测了性能,但发现人类声音定位是次优的,尤其是头部方向不确定性.
科学领域:
- 听觉神经科学 听觉神经科学
- 人类的感知 人类的感知
- 计算审计场景分析 场景分析
背景情况:
- 声音定位依赖于以头为中心的声学线索.
- 关于头部方向的感觉运动信息对于以世界为中心的声音感知至关重要.
- 头部运动减少了声音定位中的方向模糊性.
研究的目的:
- 用理想的观察者方法来模拟人类活跃的声音定位.
- 将贝叶斯模型预测与人类在自由场实验中的表现进行比较.
- 为了研究头部方向不确定性对声音定位准确性的影响.
主要方法:
- 开发了贝叶斯的理想观察者模型,用于主动声音定位.
- 集成的头部方向的感应运动信息.
- 与人类参与者进行了自由场主动定位实验.
- 将模型预测与实证人类绩效数据进行比较.
主要成果:
- 模型预测通常与人类表现一致.
- 空间分析揭示了理想观察者和人类行为之间对特定源方向的不一致.
- 头部方向的不确定性显著导致观察到的差异.
- 人类反应表现出偏差和空间分布,这些偏差和空间分布在理想观察者模型中无法完全解释.
结论:
- 人类的声音本地化,虽然一般有效,但似乎是次优的.
- 头部方向的不确定性是影响定位准确性的关键因素.
- 理想的观察者模型提供了洞察力,但并不能完全捕捉到人类活跃声音定位的复杂性.
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