基于非度量多维尺度分析的噪声声品质主观评价研究

Subjective assessment of car interior sound quality: applicability of nonmetric multidimensional scaling to sound quality research

以等响处理后双耳记录的车内噪声为例,针对非度量多维尺度分析(NMDS)是否适用于研究一致性较强的噪声声品质主观评价这一疑问进行研究。研究发现,按照评价者之间正负相关性分类处理的方法,对于运用NMDS揭示了一致性较强的复杂车内噪声声品质潜在的主观感知结构起着重要作用。采用该方法可以揭示出:车内噪声的偏好性可以作为主观感知相似性主要子维度的表示;评价者分类处理之后,两类评价者对于车内噪声的偏好性均可采用一个维度表示,并可直接采用成对比较法的直接排序法获得;一类评价者的偏好性与低沉度成正比,而另一类评价者与低沉度成反比。

With loudness-adjusted car interior noise as sound stimuli, this work focused on applicability of Nonmetric Multidimensional Scaling （NMDS） to sound quality research. It is presented that NMDS is aa effective tool to research subjective assessment of sound quality, when test people is classified by correlation between test people. With this key classification process subjective perceptive structure of stronger consistent car interior noise can be opened out. So it＇s revealed that： preference can be looked as a main subspace of similarity of car interior Sound quality; for both class of test people, preference can be one-dimensional descriptor; for one class, preference has positive relation with descriptor ＇low-frequency＇, while for another, preference has negative relation with descriptor ＇low-frequency＇.