Multi-Scale Auralization for Multimedia Analytical Feature Interaction

Nguyen NLT, Lee H, Johnson J, Ogihara M, Ren G, Beauchamp JW. Multi-Scale Auralization for Multimedia Analytical Feature Interaction. In: AES Convention 147. Audio Engineering Society; 2019. Paper 556. Available from: https://aes.org/publications/elibrary-page/?id=20579

@inproceedings{Nguyen2019_20579,
  author = {Nguyen, Nguyen Le Thanh and Lee, Hyunhwan and Johnson, Joseph and Ogihara, Mitsunori and Ren, Gang and Beauchamp, James W.},
  title = {{Multi-Scale Auralization for Multimedia Analytical Feature Interaction}},
  booktitle = {AES Convention 147},
  note = {Paper 556},
  year = {2019},
  month = oct,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=20579}
}

TY  - CPAPER
TI  - Multi-Scale Auralization for Multimedia Analytical Feature Interaction
AU  - Nguyen, Nguyen Le Thanh
AU  - Lee, Hyunhwan
AU  - Johnson, Joseph
AU  - Ogihara, Mitsunori
AU  - Ren, Gang
AU  - Beauchamp, James W.
T2  - AES Convention 147
M1  - Paper 556
PY  - 2019
DA  - 2019/10/06
UR  - https://aes.org/publications/elibrary-page/?id=20579
PB  - Audio Engineering Society
LA  - en
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.
ER  -