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Validating a perceptual distraction model using a personal two-zone sound system

机译:使用个人双区音响系统验证感知干扰模型

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摘要

This paper focuses on validating a perceptual distraction model, which aims to predict user's perceived distraction caused by audio-on-audio interference. Originally, the distraction model was trained with music targets and interferers using a simple loudspeaker setup, consisting of only two loudspeakers. Recently, the model was successfully validated in a complex personal sound-zone system with music targets and speech interferers. In this paper, a second round of validations were conducted by physically altering the sound-zone system and running listening experiments utilizing both of the two sound zones within the sound-zone system. Thus, validating the model using a different sound-zone system with both speech-on-music and music-on-speech stimuli sets. The results show that the model performance is equally good in both zones, i.e., with both speech- on-music and music-on-speech stimuli, and comparable to the previous validation round. The calculated root mean squared errors in Zone A and B were 11.3% and 10.4%, respectively, compared to the 11.0% from the previous validation round. The results further confirm that the distraction model can be used as a valuable tool in evaluating and optimizing the performance of personal sound-zone systems.
机译:本文侧重于验证感知分心模型,该模型旨在预测由音频干扰引起的用户的感知分散注意力。最初,使用简单的扬声器设置,用音乐目标和干扰培训,分散化模型培训,由两个扬声器组成。最近,该模型在具有音乐目标和语音干扰的复杂的个人声音区域系统中成功验证。在本文中,通过物理改变声音区域系统和在声音区域系统内的两个声带运行的侦听实验来进行第二轮验证。因此,使用不同的声音区域系统验证模型,其中包含语音和音乐刺激刺激。结果表明,模型性能在两个区域中同样良好,即,音乐和音乐和音乐刺激,并与先前的验证循环相当。与先前验证循环的11.0%相比,区域A和B区分别计算的均方根误差分别为11.3%和10.4%。结果进一步证实,分散化模型可以用作评估和优化个人声音区域系统性能的有价值的工具。

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