Simultaneous Manipulation of Parameters of Auditory Icons to Convey Direction, Size, and Distance: Effects on Recognition and Interpretation

Auditory icons – or environmental sounds – have the potential to convey information by non-verbal means quickly and accurately. In addition, human listeners are quick to determine many qualities of an auditory object, such as location, distance, size, and motion, from acoustics of the signal. An experiment tests these two coupled assumptions in a controlled laboratory context. Stimuli consisted of auditory icons “loaded” with information achieved through systematic manipulation of the acoustic parameters pitch, volume ramping, and reverberation. Sixty adult listeners were asked to recognize and describe four auditory icons wherein object size, distance and direction of motion were captured in the parameters of each 1-second sound. Participants were accurate at recognizing and interpreting the icons 70-80% of the time. Recognition rate was consistently high when participants responded to one, two or three parameters. However, recognition was significantly poorer when in response to all four parameters. There was a significant effect of icon type and parameter manipulation: dog bark was the most easily recognized icon, and the direction parameter interpreted most accurately. Implications of the findings for applied contexts are discussed.

[1]  S. Handel.  Listening As Introduction to the Perception of Auditory Events , 1989 .

[2]  D J Folds,et al.  Auditory signals in military aircraft: ergonomics principles versus practice. , 1986, Applied ergonomics.

[3]  R Hétu,et al.  Audibility and identification of auditory alarms in the operating room and intensive care unit. , 1993, Ergonomics.

[4]  Durand R. Begault,et al.  3-D Sound for Virtual Reality and Multimedia Cambridge , 1994 .

[5]  Stephen A. Brewster,et al.  Parallel earcons: reducing the length of audio messages , 1995, Int. J. Hum. Comput. Stud..

[6]  Gregory Kramer,et al.  Pitch and loudness interact in auditory displays: can the data get lost in the map? , 2002, Journal of experimental psychology. Applied.

[7]  E. Rosch,et al.  Family resemblances: Studies in the internal structure of categories , 1975, Cognitive Psychology.

[8]  J. Ballas.  Common factors in the identification of an assortment of brief everyday sounds. , 1993, Journal of experimental psychology. Human perception and performance.

[9]  D R Begault,et al.  Three-dimensional audio versus head-down traffic alert and collision avoidance system displays. , 1996, The International journal of aviation psychology.

[10]  S. McAdams,et al.  Auditory Cognition. (Book Reviews: Thinking in Sound. The Cognitive Psychology of Human Audition.) , 1993 .

[11]  Walter Schneider,et al.  Controlled and Automatic Human Information Processing: 1. Detection, Search, and Attention. , 1977 .

[12]  William W. Gaver.  Auditory Icons: Using Sound in Computer Interfaces , 1986, Hum. Comput. Interact..

[13]  Stephen McAdams,et al.  Recognition of sound sources and events , 1993 .

[14]  Judy Edworthy,et al.  Warning design : a research prospective , 1996 .

[15]  Meera Blattner,et al.  Earcons and Icons: Their Structure and Common Design Principles , 1989, Hum. Comput. Interact..

[16]  R. R. Patterson,et al.  Guidelines for auditory warning systems on civil aircraft , 1982 .

[17]  M. Posner,et al.  Attention and cognitive control. , 1975 .

[18]  Peter Keller,et al.  Meaning from environmental sounds: types of signal-referent relations and their effect on recognizing auditory icons. , 2004, Journal of experimental psychology. Applied.

[19]  R. Patterson.  Auditory warning sounds in the work environment. , 1990, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[20]  K. Holyoak,et al.  Encoding and recognition memory for naturalistic sounds. , 1973, Journal of experimental psychology.

[21]  Mark C. Detweiler,et al.  Iconic Reference: Evolving Perspectives and an Organizing Framework , 1993, Int. J. Man Mach. Stud..

[22]  Russell L. Martin,et al.  Learning and retention of auditory warnings , 1997 .

[23]  Walter Schneider,et al.  Controlled and automatic human information processing: II. Perceptual learning, automatic attending and a general theory. , 1977 .

[24]  A. Bregman,et al.  Demonstrations of auditory scene analysis : the perceptual organization of sound , 1995 .

[25]  William Winn,et al.  Non-Speech Sound in Human-Computer Interaction: A Review and Design Guidelines , 1994 .

[26]  J. Bartlett,et al.  Remembering environmental sounds: The role of verbalization at input , 1977, Memory & cognition.

[27]  R. M. Schafer,et al.  The tuning of the world , 1977 .

[28]  R Graham,et al.  Use of auditory icons as emergency warnings: evaluation within a vehicle collision avoidance application. , 1999, Ergonomics.

[29]  William W. Gaver,et al.  Effective sounds in complex systems: the ARKOLA simulation , 1991, CHI.

[30]  A. Edwards,et al.  Development of a standard test of musical ability for participants in auditory interface testing , 2000 .

[31]  J Edworthy,et al.  The design and implementation of non-verbal auditory warnings. , 1994, Applied ergonomics.

[32]  Catherine J. Stevens,et al.  Extracting Meaning from Sound: Nomic Mappings, Everyday Listening, and Perceiving Object Size from Frequency , 2004 .

[33]  Paul M. C. Lemmens,et al.  EFFECTS OF AUDITORY ICONS AND EARCONS ON VISUAL CATEGORIZATION: THE BIGGER PICTURE , 2001 .

[34]  Robert David Stevens,et al.  Principles for the Design of Auditory Interfaces to Present Complex Information to Blind People , 1996 .

[35]  Alan S. Brown,et al.  Information Processing and Cognition: The Loyola Symposium , 1976 .