Use of sonification in the detection of anomalous events

Mark Ballora; Robert J. Cole; Heidi Kruesi; Herbert Greene; Ganesh Mohanan; David L. Hall

doi:10.1117/12.918688

Use of sonification in the detection of anomalous events

Mark Ballora, Robert J. Cole, Heidi Kruesi, Herbert Greene, Ganesh Mohanan, David L. Hall

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Scopus citations

Abstract

In this paper, we describe the construction of a soundtrack that fuses stock market data with information taken from tweets. This soundtrack, or auditory display, presents the numerical and text data in such a way that anomalous events may be readily detected, even by untrained listeners. The soundtrack generation is flexible, allowing an individual listener to create a unique audio mix from the available information sources. Properly constructed, the display exploits the auditory system's sensitivities to periodicities, to dynamic changes, and to patterns. This type of display could be valuable in environments that demand high levels of situational awareness based on multiple sources of incoming information.

Original language	English (US)
Title of host publication	Multisensor, Multisource Information Fusion
Subtitle of host publication	Architectures, Algorithms, and Applications 2012
Publisher	SPIE
ISBN (Print)	9780819490858
DOIs	https://doi.org/10.1117/12.918688
State	Published - 2012
Event	Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2012 - Baltimore, MD, United States Duration: Apr 25 2012 → Apr 26 2012

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	8407
ISSN (Print)	0277-786X

Other

Other	Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2012
Country/Territory	United States
City	Baltimore, MD
Period	4/25/12 → 4/26/12

All Science Journal Classification (ASJC) codes

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering

Access to Document

10.1117/12.918688

Cite this

Ballora, M., Cole, R. J., Kruesi, H., Greene, H., Mohanan, G., & Hall, D. L. (2012). Use of sonification in the detection of anomalous events. In Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2012 Article 84070S (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 8407). SPIE. https://doi.org/10.1117/12.918688

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title = "Use of sonification in the detection of anomalous events",

abstract = "In this paper, we describe the construction of a soundtrack that fuses stock market data with information taken from tweets. This soundtrack, or auditory display, presents the numerical and text data in such a way that anomalous events may be readily detected, even by untrained listeners. The soundtrack generation is flexible, allowing an individual listener to create a unique audio mix from the available information sources. Properly constructed, the display exploits the auditory system's sensitivities to periodicities, to dynamic changes, and to patterns. This type of display could be valuable in environments that demand high levels of situational awareness based on multiple sources of incoming information.",

author = "Mark Ballora and Cole, {Robert J.} and Heidi Kruesi and Herbert Greene and Ganesh Mohanan and Hall, {David L.}",

year = "2012",

doi = "10.1117/12.918688",

language = "English (US)",

isbn = "9780819490858",

series = "Proceedings of SPIE - The International Society for Optical Engineering",

publisher = "SPIE",

booktitle = "Multisensor, Multisource Information Fusion",

address = "United States",

note = "Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2012 ; Conference date: 25-04-2012 Through 26-04-2012",

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Ballora, M, Cole, RJ, Kruesi, H, Greene, H, Mohanan, G & Hall, DL 2012, Use of sonification in the detection of anomalous events. in Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2012., 84070S, Proceedings of SPIE - The International Society for Optical Engineering, vol. 8407, SPIE, Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2012, Baltimore, MD, United States, 4/25/12. https://doi.org/10.1117/12.918688

Use of sonification in the detection of anomalous events. / Ballora, Mark; Cole, Robert J.; Kruesi, Heidi et al.
Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2012. SPIE, 2012. 84070S (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 8407).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Use of sonification in the detection of anomalous events

AU - Ballora, Mark

AU - Cole, Robert J.

AU - Kruesi, Heidi

AU - Greene, Herbert

AU - Mohanan, Ganesh

AU - Hall, David L.

PY - 2012

Y1 - 2012

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AB - In this paper, we describe the construction of a soundtrack that fuses stock market data with information taken from tweets. This soundtrack, or auditory display, presents the numerical and text data in such a way that anomalous events may be readily detected, even by untrained listeners. The soundtrack generation is flexible, allowing an individual listener to create a unique audio mix from the available information sources. Properly constructed, the display exploits the auditory system's sensitivities to periodicities, to dynamic changes, and to patterns. This type of display could be valuable in environments that demand high levels of situational awareness based on multiple sources of incoming information.

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M3 - Conference contribution

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SN - 9780819490858

T3 - Proceedings of SPIE - The International Society for Optical Engineering

BT - Multisensor, Multisource Information Fusion

PB - SPIE

T2 - Multisensor, Multisource Information Fusion: Architectures, Algorithms, and Applications 2012

Y2 - 25 April 2012 through 26 April 2012

ER -

Use of sonification in the detection of anomalous events

Abstract

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All Science Journal Classification (ASJC) codes

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