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NG. TH. Nguyen, H. Lee, J. Johnson, M. Ogihara, G. Ren, and JA. W.. Beauchamp, "Multi-Scale Auralization for Multimedia Analytical Feature Interaction," Engineering Brief 556, (2019 October.). doi: NG. TH. Nguyen, H. Lee, J. Johnson, M. Ogihara, G. Ren, and JA. W.. Beauchamp, "Multi-Scale Auralization for Multimedia Analytical Feature Interaction," Engineering Brief 556, (2019 October.). doi:
Abstract: Modern human-computer interaction systems use multiple perceptual dimensions to enhance intuition and efficiency of the user by improving their situational awareness. A signal processing and interaction framework is proposed for auralizing signal patterns and augmenting the visualization-focused analysis tasks of social media content analysis and annotations, with the goal of assisting the user in analyzing, retrieving, and organizing relevant information for marketing research. Audio signals are generated from video/audio signal patterns as an auralization framework, for example, using the audio frequency modulation that follows the magnitude contours of video color saturation. The integration of visual and aural presentations will benefit the user interactions by reducing the fatigue level and sharping the users’ sensitivity, thereby improving work efficiency, confidence, and satisfaction.

@article{nguyen2019multi-scale,
author={nguyen, nguyen le thanh and lee, hyunhwan and johnson, joseph and ogihara, mitsunori and ren, gang and beauchamp, james w.},
journal={journal of the audio engineering society},
title={multi-scale auralization for multimedia analytical feature interaction},
year={2019},
volume={},
number={},
pages={},
doi={},
month={october},} @article{nguyen2019multi-scale,
author={nguyen, nguyen le thanh and lee, hyunhwan and johnson, joseph and ogihara, mitsunori and ren, gang and beauchamp, james w.},
journal={journal of the audio engineering society},
title={multi-scale auralization for multimedia analytical feature interaction},
year={2019},
volume={},
number={},
pages={},
doi={},
month={october},
abstract={modern human-computer interaction systems use multiple perceptual dimensions to enhance intuition and efficiency of the user by improving their situational awareness. a signal processing and interaction framework is proposed for auralizing signal patterns and augmenting the visualization-focused analysis tasks of social media content analysis and annotations, with the goal of assisting the user in analyzing, retrieving, and organizing relevant information for marketing research. audio signals are generated from video/audio signal patterns as an auralization framework, for example, using the audio frequency modulation that follows the magnitude contours of video color saturation. the integration of visual and aural presentations will benefit the user interactions by reducing the fatigue level and sharping the users’ sensitivity, thereby improving work efficiency, confidence, and satisfaction.},}

TY - paper
TI - Multi-Scale Auralization for Multimedia Analytical Feature Interaction
SP - EP -
AU - Nguyen, Nguyen Le Thanh
AU - Lee, Hyunhwan
AU - Johnson, Joseph
AU - Ogihara, Mitsunori
AU - Ren, Gang
AU - Beauchamp, James W.
PY - 2019
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - October 2019 TY - paper
TI - Multi-Scale Auralization for Multimedia Analytical Feature Interaction
SP - EP -
AU - Nguyen, Nguyen Le Thanh
AU - Lee, Hyunhwan
AU - Johnson, Joseph
AU - Ogihara, Mitsunori
AU - Ren, Gang
AU - Beauchamp, James W.
PY - 2019
JO - Journal of the Audio Engineering Society
IS -
VO -
VL -
Y1 - October 2019
AB - Modern human-computer interaction systems use multiple perceptual dimensions to enhance intuition and efficiency of the user by improving their situational awareness. A signal processing and interaction framework is proposed for auralizing signal patterns and augmenting the visualization-focused analysis tasks of social media content analysis and annotations, with the goal of assisting the user in analyzing, retrieving, and organizing relevant information for marketing research. Audio signals are generated from video/audio signal patterns as an auralization framework, for example, using the audio frequency modulation that follows the magnitude contours of video color saturation. The integration of visual and aural presentations will benefit the user interactions by reducing the fatigue level and sharping the users’ sensitivity, thereby improving work efficiency, confidence, and satisfaction.