Communication skills training intervention based on automated recognition of nonverbal signals

Pereira, Monica and Hone, Kate (2021) Communication skills training intervention based on automated recognition of nonverbal signals. In: CHI Conference on Human Factors in Computing Systems, 8-13 May 2021, Yokohama Japan.

Preview

Text 3411764.3445324.pdf - Published Version Download (1MB) | Preview

Abstract / Description

There have been promising studies that show a potential of providing social signal feedback to improve communication skills. However, these studies have primarily focused on unimodal methods of feedback. In addition to this, studies do not assess whether skills are maintained after a given time. With a sample size of 22 this paper investigates whether multimodal social signal feedback is an efective method of improving communication in the context of media interviews. A pre-post experimental evaluation of media skills training intervention is presented which compares standard feedback with augmented feedback based on automated recognition of multimodal social signals. Results revealed signifcantly diferent training efects between the two conditions. However, the initial experiment study failed to show signifcant diferences in human judgement of performance. A 6-month follow-up study revealed human judgement ratings were higher for the experiment group. This study suggests that augmented selective multimodal social signal feedback is an efective method for communication skills training.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	** From Crossref proceedings articles via Jisc Publications Router
Uncontrolled Keywords:	social signals; communication skills training; media interviews; of-the-shelf emotion recognition technology
Subjects:	100 Philosophy & psychology > 150 Psychology 300 Social sciences
Department:	School of Social Sciences (to June 2021) School of Social Sciences and Professions
SWORD Depositor:	Pub Router
Depositing User:	Pub Router
Date Deposited:	28 May 2021 10:17
Last Modified:	28 May 2021 10:17
URI:	https://repository.londonmet.ac.uk/id/eprint/6710

Downloads

Actions (login required)

View Item