AutoManner: An Automated Interface for Making Public Speakers Aware of Their Mannerisms

Many individuals exhibit unconscious body movements called mannerisms while speaking. These repeated changes often distract the audience when not relevant to the verbal context. We present an intelligent interface that can automatically extract human gestures using Microsoft Kinect to make speakers aware of their mannerisms. We use a sparsitybased algorithm, Shift Invariant Sparse Coding, to automatically extract the patterns of body movements. These patterns are displayed in an interface with subtle question and answerbased feedback scheme that draws attention to the speaker’s body language. Our formal evaluation with 27 participants shows that the users became aware of their body language after using the system. In addition, when independent observers annotated the accuracy of the algorithm for every extracted pattern, we find that the patterns extracted by our algorithm is significantly (p < 0.001) more accurate than just random selection. This represents a strong evidence t...

• Type: Journal
• Year: 2016
• Where: IUI
• Authors: Mohammad Iftekhar Tanveer, Ru Zhao, Kezhen Chen, Zoe Tiet, Mohammed (Ehsan) Hoque
• Keywords: IUI 2016, Software Engineering