Task Boundary Inference via Topic Modeling to Predict Interruption Timings for Human-Machine Teaming.

Human-machine teaming aims to meld human cognitive strengths with the unique capabilities of smart machines. An issue within human-machine teaming is a lack of communication skills on the part of the machine such as the inability to know when to interrupt human teammates. A proposed solution to this issue is an intelligent interruption system that monitors the spoken communication of human teammates and predicts appropriate times to interrupt without disrupting the teaming interaction. The current research expands on a prosody-only task boundary model as an intelligent interruption system with a topic-only task boundary model. The topic-only task boundary model outperforms the prosody-only model with a 9.5% increase in the F1 score, but is limited in its ability to process topical data in real-time, a previous benefit of the prosody-only task boundary model.