Data collection and analysis techniques for evaluating the perceptual qualities of auditory stimuli
Data collection and analysis techniques for evaluating the perceptual qualities of auditory stimuli
复制标题
用于评估听觉刺激感知质量的数据收集和分析技术
DOI：
10.1145/1101530.1101550
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发表时间：
1998
期刊：
影响因子：
--
通讯作者：
T. Caudell
中科院分区：
文献类型：
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作者：
Terri L. Bonebright;N. Miner;T. Goldsmith;T. Caudell
本文描述了评估听觉刺激的感知特性的一般方法框架。该框架提供了分析技术，可以确保有效地利用声音的各种应用，包括虚拟现实和数据超声系统。具体来说，我们讨论了单个听觉刺激的感知质量的数据收集技术，包括识别任务、基于上下文的评级和属性评级。此外，我们提出了比较听觉刺激的方法，如区分任务、相似性评级和分类任务。最后，我们讨论了关注刺激之间感知关系的统计技术，如多维尺度（MDS）和探路者分析。这些方法是为非感性实验方法专家提供的有组织和系统的方法的起点，而不是作为执行统计技术和数据收集方法的完整手册。我们希望这篇论文将有助于促进知觉研究者、设计师、工程师和其他人员在开发有效听觉显示方面的进一步跨学科合作。
This paper describes a general methodological framework for evaluating the perceptual properties of auditory stimuli. The framework provides analysis techniques that can ensure the effective use of sound for a variety of applications, including virtual reality and data sonification systems. Specifically, we discuss data collection techniques for the perceptual qualities of single auditory stimuli including identification tasks, context-based ratings, and attribute ratings. In addition, we present methods for comparing auditory stimuli, such as discrimination tasks, similarity ratings, and sorting tasks. Finally, we discuss statistical techniques that focus on the perceptual relations among stimuli, such as Multidimensional Scaling (MDS) and Pathfinder Analysis. These methods are presented as a starting point for an organized and systematic approach for nonexperts in perceptual experimental methods, rather than as a complete manual for performing the statistical techniques and data collection methods. It is our hope that this paper will help foster further interdisciplinary collaboration among perceptual researchers, designers, engineers, and others in the development of effective auditory displays.