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Affective Design of Warning Sounds used in Windows Operating Systems  

Hong, Seung W. (Korea University Department of Industrial Systems and Information Engineering)
Jung, Eui S. (Korea University Department of Industrial Systems and Information Engineering)
Park, Sungjoon (NamSeoui University Department of Industrial and Environmental Systems Engineering)
Choi, Dong S. (Korea University Department of Industrial Systems and Information Engineering)
Publication Information
Journal of Korean Institute of Industrial Engineers / v.29, no.4, 2003 , pp. 259-270 More about this Journal
Abstract
In order to properly design warning sounds that are affectively suitable to computer users, warning sounds used in Windows operating system were analyzed in terms of their sound properties; frequency band, spectral characteristics and physical intensity. A total of 36 warning sounds (3*4*3) were generated and tested with respect to three experimental variables. Among 178 collected affective adjectives that are related to hearing and sounds, seven representative affective adjectives were abstracted by statistical grouping techniques. In the experiment, subjective preference tests were performed for the 36 warning sounds according to the seven affective factors. From the result, the affective factors were again grouped into three major factors and the 60dB boost-type warning sounds at the low frequency band were, in general, the most preferred. followed by the 70dB cut-type sounds at the middle frequency band. These warning sounds have a characteristic of boost power spectrum below 1000Hz frequency band and received good scores on simplicity, clarity and accurateness.
Keywords
windows operating systems; warning sounds; factor analysis; multi-dimensional scaling;
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  • Reference
1 Choi, M-J. (1997), Sensitivity Side and Practical Use of Sound, The lnstitute of Electronics Engineers of Korea, 24(11), 1317-1333.
2 Heo, M-H. (2000), Multi-variance Data Analysis, Free Academy.
3 Jung, M-J., Hwang, S-Y., & Choi, K-S. (1988), Power Spectral Estimation of Background EEG with LMS PHD, Journal of KOSOMBE, 101-107.
4 Takeshi, I. & Takeo, H. (2000), The Impact of Sound Quality on Annoyance caused by Road Traffic Noise: an Influence of Frequency Spectra on Annoyance, Society of Automotive Engineers of Japan, Inc. & Elsevier Science B.V., 21, 225-230.
5 Kim, H-D., Kim, J-e. & Kim, J-T. (1992), A study on the Changes in the Electromyographic Power Spectrum of the Masticatory Muscles during Orthodontic Treatment of the Class III Malocclusion Children, Korean Academy of Pediatric Denti..try, 19(1), 45-62.
6 Cho, M-J. (2002) A Study on the Human Response for Sound in Living Environments with Purpose of Establishing Related DB, Korea Research Institute of Standards and Science, 13-14
7 Lee, S-M. (2000), Basis of Factor Analysis, Education Technography. Min, Y-K., & Son, J-H. (1999), Analysis of Emotional Characteristics on Life Environmental Noise I: Structural Analysis of Noise Adjectives, Korean Journal of The Science of Emotion & Sensibility, 2(1), 69-75.   과학기술학회마을
8 Park, M-C., Shin, S-G .. , Han, K-H., & Whang, S-M. (1998), Measuring Meaning of Korean Adjectives and Colors, Korean Journal of The Science of Emotion & Sensibility, 1(2), 1-11.
9 Lee, K-H., Kim, B-J, & Jeong, I-S. (2001), Effect of Multimodal Stimuli on Human Sensibility, Korean Journal of The Science of Emotion & Sensibility, 4(1), 43-51.
10 Anders, K., Ulf, L., Maria, T., Lena, S. & Elisabeth, A. (1996), The Effect Nonphysical Noise Characteristics, ongoing Task and Noise Sensitivity on Annoyance and Distraction due to Noise at Work, Journal of Environmental Psychology, 16, 123-136.
11 Park, Y-K., Kim, J-K., Jeon, Y-W., & Cho, A. (2002), Evaluation of Synthetic Voice which is Agreeable to the Ear Using Sensibility Ergonomics Method, Journal of the Ergonomics Society of Korea, 21(1), 51-65.
12 Rungtai Lin., C. Y. Lin, & Joan, W. (1996), An Application of Multidimensional Scaling in Product Semantics, International of Industrial Ergonomics, 18, 193-204.
13 Wilkins, P. A. (1984), A Field Study to Assess the Effects of Wearing Hearing Protectors on the perception of Warning Sounds in an Industrial Environment, Applied Acoustics, 17(6), 413-437.
14 Han, M-H., & Kim, S-W. (1997), An Analysis on the Structure of Measuring for Amenities of Sound Environment III, Acoustical Society of Korea, 17(6), 67-73.
15 Son, Y-J. (1992), Tributary System of Sense Adjective, The Institute of Urimalgeul, 10(1), 127-154.
16 Judy, E. & Rachael H. (1999), Learning Auditory Warning: The Effects of Sound Type, Verbal Labelling and Imagery on the Identification of Alarm Sounds, lnternational Journal of lndustrial Ergonomics, 24, 603-618.   DOI   ScienceOn
17 Won, T-Y, & Jeong, S-W. (2000), Korean SPSS 10K Statistical Research Analysis, SPSS Academy.
18 Christopher, D. Wickens. (1998), An Introduction to Human Factors Engineeming, Addison-Wisley Educational Publishers, 113-144
19 Kim, S-W., Jang, G-S., Jong, K-Y., & Han, M-H. (1993), A Study on the Classification of Adjectives for Psychological Evaluation of Sound, The Korean Society for Noise and Vibration Engineerning, 3(4), 361-371.