声音粗度的声学估计
1Division of Cognitive Science, Department of Philosophy, Lund University, Box 192, SE- 221 00, Lund, Sweden. andrey.anikin@lucs.lu.se.
Attention, perception & psychophysics
|April 28, 2025
概括
测量声音粗度的标准化方法对于一致的研究至关重要. 新的算法从调制光谱中估计了粗度,解释了50%的听众评分差异,并帮助进行通信分析.
科学领域:
- 声学 声学 在声学方面
- 精神声学是一种精神声学.
- 生物声学是一种生物声学.
背景情况:
- 声音粗是人类和动物交流中的一个关键的感知特征.
- 它在社会统治和尖叫等紧急信号中发挥着作用.
- 为了可靠的粗度研究,需要标准化的测量方法.
研究的目的:
- 审查关于粗度估计的现有文献.
- 介绍和验证用于声粗度测量的新算法.
- 提供标准化工具,用于语音中的粗度分析.
主要方法:
- 关于粗度估计技术的文献综述.
- 使用602个由162名听众评价的人类声学样本进行感知实验.
- 开发和优化使用调制光谱的两个算法 (马/巴特沃思波器和短时间里叶变换).
主要成果:
- 开发了两个声学算法来估计声音粗度.
- 这两种算法都解释了人类听众评分差异的约50%.
- 对于粗感知的最佳调制频率范围被确定为 [50, 200] Hz.
结论:
- 开发的算法提供了一种标准化和客观的方法来测量声音粗度.
- 调制和粗度谱图可以可视化粗度动态.
- 这些算法可在开源R库的soundgen中使用,数据公开可用于基准测试.
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