通过自动驾驶音响合成研究语音烦
1Division of Cognitive Science, Department of Philosophy, Lund University.
Journal of experimental psychology. General
|February 23, 2026
概括
烦人的发音是由信号密度和声学事件速率决定的. 快速,不可预测的声音序列有效地发出警报,而不会引起过度烦,与连续的强烈信号不同.
科学领域:
- 听觉感知是一种听觉感知.
- 生物声学是一种生物声学.
- 精神声学是一种精神声学.
背景情况:
- 应急和报警信号必须引起注意,而不会引起习惯.
- 侵入性信号可以引起压力和烦,需要研究它们的感知决定因素.
- 了解声音的烦是设计有效和不那么刺激的听觉警报的关键.
研究的目的:
- 调查声学和时间特征,使发声分散注意力和烦人.
- 开发和利用一种新的实验范式,即自控声合成 (SSSS),用于研究语音感知.
- 确定合成发音中声音烦的主要决定因素.
主要方法:
- 为参与者开发了自动引导的声音合成 (SSSS),以创建现实的合成发音.
- 参与者操纵了声音序列的音调,声音质量和时间结构 (例如,吠叫,呼叫,喊叫).
- 独立的听众组评估了合成的发音对烦.
主要成果:
- 声音烦主要取决于信号密度 (发声时间的比例,不规则的发音) 和声学事件率 (个体呼叫,质量变化).
- 在SSSS实验中,不可预测的时间结构增加了,但没有显著影响烦评级.
- 持续的,强烈的信号 (例如,婴儿的哭声) 引起了最大的声应力,很难忽视.
结论:
- 快速和/或不可预测的速度短声信号的序列是最佳的警报没有不必要的烦.
- 通过SSSSS方法,可以创建和研究比以前更广泛的声音刺激.
- 这些发现在研究人类/动物通信信号和用于听觉警报的声音设计方面具有广泛的应用.
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