Neo-Noumena: Augmenting Emotion Communication

Abstract: The subjective experience of emotion is notoriously difficult to interpersonally communicate. We believe that technology can challenge this notion through the design of neuroresponsive systems for interpersonal communication. We explore this through "Neo-Noumena", a communicative neuroresponsive system that uses brain-computer interfacing and artificial intelligence to read one’s emotional states and dynamically represent them to others in mixed reality through two head-mounted displays. In our study five participant pairs were given Neo-Noumena for three days, using the system freely. Measures of emotional competence demonstrated a statistically significant increase in participants’ ability to interpersonally regulate emotions. Furthermore, participant interviews revealed themes regarding Spatiotemporal Actualization, Objective Representation, and Preternatural Transmission. We also suggest design strategies for future augmented emotion communication systems. We intend that work gives guidance towards a future in which our ability to interpersonally communicate emotion is augmented beyond traditional experience.

05/01/2021

On the Utility of Audiovisual Dialog Technologies and Signal Analytics for Real-time Remote Monitoring of Depression Biomarkers

Tianmin Shu, Abhishek Bhandwaldar, Chuang Gan and
Kevin Smith, Shari Liu, Dan Gutfreund, Elizabeth Spelke, Josh Tenenbaum, Tomer Ullman

Inferring Emotion from Large-scale Internet Voice Data: A Semi-supervised Curriculum Augmentation based Deep Learning Approach

Suping Zhou, Jia Jia, Zhiyong Wu and
Zhihan Yang, Yanfeng Wang, Wei Chen, Fanbo Meng, Shuo Huang, Jialie Shen, Xiaochuan Wang

Keerthiram Murugesan, Mattia Atzeni, Pavan Kapanipathi and
Pushkar Shukla, Sadhana Kumaravel, Gerald Tesauro, Kartik Talamadupula, Mrinmaya Sachan, Murray Campbell

Musical features and properties, Musical affect, emotion, and mood, Applications, Music recommendation and playlist generation, Music retrieval systems, Domain knowledge, Machine learning/Artificial intelligence for music, MIR tasks, Automatic classification, Pattern matching and detection

3:15

04/07/2020

Navonil Majumder, Pengfei Hong, Shanshan Peng and
Jiankun Lu, Deepanway Ghosal, Alexander Gelbukh, Rada Mihalcea, Soujanya Poria

MEISD: A Multimodal Multi-Label Emotion, Intensity and Sentiment Dialogue Dataset for Emotion Recognition and Sentiment Analysis in Conversations

Sina Mohseni, Fan Yang, Shiva Pentyala and
Mengnan Du, Yi Liu, Nic Lupfer, Xia Hu, Shuiwang Ji, Eric Ragan

Keywords Paper

Qualitative and quantitative studies of social media, Credibility of online content, Trust, reputation, recommendation systems, Human computer interaction, social media tools, navigation and visualization

8:01

08/12/2020