A series of controlled listening tests were conducted on 30 different models of in-ear (IE) headphones to measure their relative sound quality. A total of 71 listeners both trained and untrained rated the headphones on a 100-point preference scale using a multiple stimulus method with a hidden reference and low anchor. A virtual headphone test method was used wherein each headphone was simulated over a high-quality replicator headphone equalized to match their measured magnitude response. Leakage was monitored and eliminated for each subject. The results revealed both trained and untrained listeners preferred the hidden reference, which was the replicator headphone equalized to our new IE headphone target response curve. The further the other headphones deviated from the target response, the less they were preferred. Part two of this paper develops a statistical model that predicts the headphone preference ratings based on their acoustic measurements.
对30种不同型号的入耳式(IE)耳机进行了一系列可控的听力测试,以测量评价其相对音质。 共有71名接受过听音评价训练的人员和未受过训练的普通听众参与测试,采用多激励隐含基准和锚测试方法,以100分制偏好打分表对耳机进行评级。我们使用虚拟耳机测试方法,用高质量的复制耳机模拟各个被测耳机,复制耳机被调整到与被测耳机的实测幅度响应一致。监测并排除每个被试耳机的泄漏。实验结果显示,无论受过或没受过训练的听众都喜欢隐含基准(的听感),就是调整成与了我们新的IE耳机目标响应曲线一样的复制耳机。对其他耳机,偏离目标响应(曲线)越远,参与评测的人员就越不喜欢。本文的第二部分提出了一个基于声学测量参数预测耳机偏好打分的统计模型。
https://www.aes.org/e-lib/browse.cfm?elib=19237
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