Communication Skills Training Intervention Based on Automated Recognition of Nonverbal Signals

要旨

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 effective 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 significantly different training effects between the two conditions. However, the initial experiment study failed to show significant differences 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 effective method for communication skills training.

著者
Monica Pereira
London Metropolitan University, London, United Kingdom
Kate Hone
Brunel University London, London, United Kingdom
DOI

10.1145/3411764.3445324

論文URL

https://doi.org/10.1145/3411764.3445324

動画

会議: CHI 2021

The ACM CHI Conference on Human Factors in Computing Systems (https://chi2021.acm.org/)

セッション: Input / Spatial Interaction / Practice Support

[A] Paper Room 10, 2021-05-11 17:00:00~2021-05-11 19:00:00 / [B] Paper Room 10, 2021-05-12 01:00:00~2021-05-12 03:00:00 / [C] Paper Room 10, 2021-05-12 09:00:00~2021-05-12 11:00:00
Paper Room 10
13 件の発表
2021-05-11 17:00:00
2021-05-11 19:00:00
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