用自适应听感测试法，帮不懂声学的普通人选出最满意的耳机音效。
An Adaptive Method for Target Curve Selection
- 基于自适应配对评分的听感测试，动态调整对比方案。
- 在20多名消费者上验证，算法能稳定收敛到偏好目标。
- 适合音频产品设计中挖掘非专业用户的主观偏好。
本文将交互式差分进化（IDE）算法引入音频领域，用于从消费者中识别理想的耳戴式耳机频响目标。方法基于自适应配对评分听感测试范式（带评分量表的配对比较），详细阐述了算法及其参数设置。同时，报告了三轮听感实验中超过20名参与者的数据，并通过两个收敛性指标评估算法在该未测试领域的表现。结果表明，该方法具备收敛能力，有助于从无专业知识的用户中提取频响偏好。
原文摘要 · Abstract (English)
In this paper, we introduce an adaptation of the "Interactive Differential Evolution" (IDE) algorithm to the audio domain for the task of identifying the preferred over-the-ear headphone frequency response target among consumers. The method is based on data collection using an adaptive paired rating listening test paradigm (paired comparison with a scale). The IDE algorithm and its parameters are explained in detail. Additionally, data collected from three listening experiments with more than 20 consumers is presented, and the algorithm's performance in this untested domain is investigated on the basis of two convergence measures. The results indicate that this method can converge and may ease the task of 'extracting' frequency response preference from untrained consumers.
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