Social Intelligence Modeling using Wearable Devices

Abstract

Social Signal Processing techniques have given the opportunity to analyze in-depth human behavior in social face-to-face interactions. With recent advancements, it is henceforth possible to use these techniques to augment social interactions, especially the human behavior in oral presentations. The goal of this paper is to train a computational model able to provide a relevant feedback to a public speaker concerning his coverbal communication. Hence, the role of this model is to augment the social intelligence of the orator and then the relevance of his presentation. To this end, we present an original interaction setting in which the speaker is equipped with only wearable devices. Several coverbal modalities have been extracted and automatically annotated namely speech volume, intonation, speech rate, eye gaze, hand gestures and body movements. An offline report was addressed to participants containing the performance scores on the overall modalities. In addition, a post-experiment study was conducted to collect participant's opinions on many aspects of the studied interaction and the results were rather positive. Moreover, we annotated recommended feedbacks for each presentation session, and to retrieve these annotations, a Dynamic Bayesian Network model was trained using as inputs the multimodal performance scores. We will show that our assessment behavior model presents good performances compared to other models.

Scalability, Sustainability, and Ethicality of Multimodal Learning Analytics

“…Smart Glasses [42] that cost around $700 each. For positioning sensors, while the unit price of each positioning tag can be as low as $20 (e.g., Tatwah Mango BLE-WB200 wristband [72]), a complete positioning tracking system is expensive [3,24,26,39], ranging from $1,500 to $19,000, depending on the number of tracked students [72].…”

A Survey on Formal Verification and Validation Techniques for Internet of Things

“…The Internet of Things (IoT) has evolved significantly over the past few decades, from simple machine-to-machine (M2M) communication to a vast network of interconnected devices and systems [42][43][44][45][46][47]. The evolution of the IoT has been driven by advancements in communication technologies, such as wireless networks, sensors, and cloud computing, as well as the increasing demand for automation and real-time monitoring in various industries [48][49][50][51][52].…”

Wearables and Social Signal Processing for Smarter Public Presentations

“…Note that this article is an extension to our previous article published in [37]. In this paper, we complete that study with 3 main contributions, which are: a comparative study between our DBN design and classical J48/MLP/SVM classifiers; a subjective evaluation of presenter skills with a discussion in regards to our automatic evaluation; and a complementary study about using DBScan versus K-means algorithm in the DBN design process.…”

“…Oral communication is considered one of the most valued interpersonal skills in variety of domains [37], such as education, business and politics [30]. This task of public speaking stresses many people and was featured in many surveys as their number one fear, even higher than death [50].…”