Augmenting Social Interactions

Abstract

Figure 1. Concept of the Logue system: A user wearing an HMD while giving a public speech (left). Using various sensors and social signal processing techniques (not illustrated), the user receives realtime feedback on his own behaviour superimposed on field of view (right). ABSTRACTNonverbal and unconscious behaviour is an important component of daily human-human interaction. This is especially true in situations such as public speaking, job interviews or information sensitive conversations, where researchers have shown that an increased awareness of one's behaviour can improve the outcome of the interaction. With wearable technology, such as Google Glass, we now have the opportunity to augment social interactions and provide realtime feedback on one's behaviour in an unobtrusive way. In this paper we present Logue, a system that provides realtime feedback on the presenters' openness, body energy and speech rate during public speaking. The system analyses the user's nonverbal behaviour using social signal processing techniques and gives visual feedback on a head-mounted display. We conducted two user studies with a staged and a real presentation scenario which yielded that Logue's feedback was perceived helpful and had a positive impact on the speaker's performance.

Throwaway Citation of Prior Work Creates Risk of Bad HCI Research

“…'lovely'), with negative facial expression or tone of voice, participants in 93% of cases saw this as a negative communication overall. This myth continues to be presented in published HCI work as fact, for example "nonverbal behaviours, such as gestures, facial expressions or the way we use our voice, play a more significant role during an interaction than its verbal counterpart" [4], citing either Mehrabian, or affective computing work which can be traced back to Mehrabian.…”

Anticipating Averted Gaze in Dyadic Interactions

“…Anticipating averted gaze also enables new applications supporting human-human interactions. Current research on real-time feedback in social interactions is limited to intervening after a target behaviour has been observed [Damian et al 2015;Schiavo et al 2014]. With averted gaze anticipation, feedback systems could intervene earlier, not allowing the undesired behaviour to occur in the first place.…”

REsCUE

“…Based on the methods to understand human nonverbal behavior in real-time, some studies have proposed systems to provide real-time feedback on social interactions [17,40,43,44,52,56,58]. For example, Rhema [56] is designed to help people with public presentations by providing feedback in real-time via Google Glass based on a speaker's volume and speaking rate.…”

“…For example, Rhema [56] is designed to help people with public presentations by providing feedback in real-time via Google Glass based on a speaker's volume and speaking rate. Logue [17] addressed a similar situation by providing feedback via head-mounted display based on body energy and openness calculated from hand positions. For group discussions, Tausczik et al [58] proposed a system to analyze the communication patterns of participants and to provide linguistic feedback for improving teamwork.…”