Multi-Scale Auralization for Multimedia Analytical Feature Interaction

Nguyen Le Thanh, James W. Beauchamp, Hyunhwan “Aiden” Lee, Gang Ren, Joseph Johnson, and Mitsunori Ogihara, “Multi-Scale Auralization for Multimedia Analytical Feature Interaction”

  • 2019 Audio Engineering Society (AES) 147th Pro Audio Convention in New York, NY.
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 for 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.

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