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Title: Data Collection and Analysis Techniques for Evaluating the Perceptual Qualities of Auditory Stimuli

Abstract

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 non-experts 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.

Authors:
; ; ;
Publication Date:
Research Org.:
Sandia National Laboratories, Albuquerque, NM, and Livermore, CA
Sponsoring Org.:
USDOE
OSTI Identifier:
1915
Report Number(s):
SAND98-2568C
ON: DE00001915
DOE Contract Number:  
AC04-94AL85000
Resource Type:
Conference
Resource Relation:
Conference: International Conference on Auditory Displays; Glasgow, UK; 01/01-04/1998
Country of Publication:
United States
Language:
English
Subject:
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; 99 MATHEMATICS, COMPUTERS, INFORMATION SCIENCE, MANAGEMENT, LAW, MISCELLANEOUS; Acoustic Detection; Acoustic Monitoring; Speech; Computerized Simulation; Computer Graphics

Citation Formats

Bonebright, T.L., Caudell, T.P., Goldsmith, T.E., and Miner, N.E. Data Collection and Analysis Techniques for Evaluating the Perceptual Qualities of Auditory Stimuli. United States: N. p., 1998. Web.
Bonebright, T.L., Caudell, T.P., Goldsmith, T.E., & Miner, N.E. Data Collection and Analysis Techniques for Evaluating the Perceptual Qualities of Auditory Stimuli. United States.
Bonebright, T.L., Caudell, T.P., Goldsmith, T.E., and Miner, N.E. Tue . "Data Collection and Analysis Techniques for Evaluating the Perceptual Qualities of Auditory Stimuli". United States. https://www.osti.gov/servlets/purl/1915.
@article{osti_1915,
title = {Data Collection and Analysis Techniques for Evaluating the Perceptual Qualities of Auditory Stimuli},
author = {Bonebright, T.L. and Caudell, T.P. and Goldsmith, T.E. and Miner, N.E.},
abstractNote = {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 non-experts 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.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {1998},
month = {11}
}

Conference:
Other availability
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