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由有经验的听众、音乐家和非音乐家对录制和合成的撞击声进行分类和识别。

Classification and identification of recorded and synthesized impact sounds by practiced listeners, musicians, and nonmusicians.

作者信息

Lutfi Robert A, Oh Eunmi, Storm Eileen, Alexander Joshua M

机构信息

Department of Communicative Disorders and Waisman Center, University of Wisconsin, Madison, Wisconsin 53706, USA.

出版信息

J Acoust Soc Am. 2005 Jul;118(1):393-404. doi: 10.1121/1.1931867.

DOI:10.1121/1.1931867
PMID:16119360
Abstract

Three experiments were conducted to test the viability of a low-parameter modal model for synthesizing impact sounds to be used in commercial and psychoacoustic research. The model was constrained to have four physically based parameters dictating the amplitude, frequency, and decay of modes. The values of these parameters were selected by ear to roughly match the recordings of ten different resonant objects suspended by hand and struck with different mallets. In experiment 1, neither 35 professional musicians nor 187 college undergraduates could identify which of the two matched sounds was the real recording with better than chance accuracy, though significantly better than chance performance was obtained when modal parameters were selected without the previously imposed physical constraints. In experiment 2, the undergraduates identified the source corresponding to the recorded and synthesized sounds with the same level of accuracy and largely the same pattern of errors. Finally, experiment 3 showed highly practiced listeners to be largely insensitive to changes in the acoustic waveform resulting from an increase in the number of free parameters used in the modal model beyond 3. The results suggest that low-parameter, modal models might be exploited meaningfully in many commercial and research applications involving human perception of impact sounds.

摘要

进行了三项实验,以测试一种低参数模态模型在合成用于商业和心理声学研究的撞击声方面的可行性。该模型被限制为具有四个基于物理的参数,这些参数决定了模态的振幅、频率和衰减。这些参数的值通过听觉选择,以大致匹配十个不同的用手悬挂并用不同鼓槌敲击的共振物体的录音。在实验1中,35名专业音乐家和187名大学生都无法以高于随机概率的准确率识别出两个匹配声音中哪一个是真实录音,不过当在没有先前施加的物理约束的情况下选择模态参数时,获得了显著高于随机概率的表现。在实验2中,大学生以相同的准确率和大致相同的错误模式识别出与录制声音和合成声音相对应的声源。最后,实验3表明,训练有素的听众对模态模型中使用的自由参数数量增加到3以上所导致的声学波形变化基本不敏感。结果表明,低参数模态模型可能在许多涉及人类对撞击声感知的商业和研究应用中得到有意义的利用。

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